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Publisher: John Wiley and Sons   (Total: 1589 journals)

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Showing 1 - 200 of 1589 Journals sorted alphabetically
Abacus     Hybrid Journal   (Followers: 12, SJR: 0.48, h-index: 22)
About Campus     Hybrid Journal   (Followers: 5)
Academic Emergency Medicine     Hybrid Journal   (Followers: 65, SJR: 1.385, h-index: 91)
Accounting & Finance     Hybrid Journal   (Followers: 48, SJR: 0.547, h-index: 30)
ACEP NOW     Free   (Followers: 1)
Acta Anaesthesiologica Scandinavica     Hybrid Journal   (Followers: 53, SJR: 1.02, h-index: 88)
Acta Archaeologica     Hybrid Journal   (Followers: 168, SJR: 0.101, h-index: 9)
Acta Geologica Sinica (English Edition)     Hybrid Journal   (Followers: 3, SJR: 0.552, h-index: 41)
Acta Neurologica Scandinavica     Hybrid Journal   (Followers: 5, SJR: 1.203, h-index: 74)
Acta Obstetricia et Gynecologica Scandinavica     Hybrid Journal   (Followers: 15, SJR: 1.197, h-index: 81)
Acta Ophthalmologica     Hybrid Journal   (Followers: 6, SJR: 0.112, h-index: 1)
Acta Paediatrica     Hybrid Journal   (Followers: 56, SJR: 0.794, h-index: 88)
Acta Physiologica     Hybrid Journal   (Followers: 6, SJR: 1.69, h-index: 88)
Acta Polymerica     Hybrid Journal   (Followers: 9)
Acta Psychiatrica Scandinavica     Hybrid Journal   (Followers: 37, SJR: 2.518, h-index: 113)
Acta Zoologica     Hybrid Journal   (Followers: 7, SJR: 0.459, h-index: 29)
Acute Medicine & Surgery     Hybrid Journal   (Followers: 5)
Addiction     Hybrid Journal   (Followers: 36, SJR: 2.086, h-index: 143)
Addiction Biology     Hybrid Journal   (Followers: 14, SJR: 2.091, h-index: 57)
Adultspan J.     Hybrid Journal   (SJR: 0.127, h-index: 4)
Advanced Energy Materials     Hybrid Journal   (Followers: 26, SJR: 6.411, h-index: 86)
Advanced Engineering Materials     Hybrid Journal   (Followers: 26, SJR: 0.81, h-index: 81)
Advanced Functional Materials     Hybrid Journal   (Followers: 51, SJR: 5.21, h-index: 203)
Advanced Healthcare Materials     Hybrid Journal   (Followers: 14, SJR: 0.232, h-index: 7)
Advanced Materials     Hybrid Journal   (Followers: 295, SJR: 9.021, h-index: 345)
Advanced Materials Interfaces     Hybrid Journal   (Followers: 6, SJR: 1.177, h-index: 10)
Advanced Optical Materials     Hybrid Journal   (Followers: 7, SJR: 2.488, h-index: 21)
Advanced Science     Open Access   (Followers: 5)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 17, SJR: 2.729, h-index: 121)
Advances in Polymer Technology     Hybrid Journal   (Followers: 13, SJR: 0.344, h-index: 31)
Africa Confidential     Hybrid Journal   (Followers: 21)
Africa Research Bulletin: Economic, Financial and Technical Series     Hybrid Journal   (Followers: 13)
Africa Research Bulletin: Political, Social and Cultural Series     Hybrid Journal   (Followers: 11)
African Development Review     Hybrid Journal   (Followers: 33, SJR: 0.275, h-index: 17)
African J. of Ecology     Hybrid Journal   (Followers: 16, SJR: 0.477, h-index: 39)
Aggressive Behavior     Hybrid Journal   (Followers: 15, SJR: 1.391, h-index: 66)
Aging Cell     Open Access   (Followers: 11, SJR: 4.374, h-index: 95)
Agribusiness : an Intl. J.     Hybrid Journal   (Followers: 3, SJR: 0.627, h-index: 14)
Agricultural and Forest Entomology     Hybrid Journal   (Followers: 16, SJR: 0.925, h-index: 43)
Agricultural Economics     Hybrid Journal   (Followers: 45, SJR: 1.099, h-index: 51)
AIChE J.     Hybrid Journal   (Followers: 32, SJR: 1.122, h-index: 120)
Alcoholism and Drug Abuse Weekly     Hybrid Journal   (Followers: 7)
Alcoholism Clinical and Experimental Research     Hybrid Journal   (Followers: 7, SJR: 1.416, h-index: 125)
Alimentary Pharmacology & Therapeutics     Hybrid Journal   (Followers: 33, SJR: 2.833, h-index: 138)
Alimentary Pharmacology & Therapeutics Symposium Series     Hybrid Journal   (Followers: 3)
Allergy     Hybrid Journal   (Followers: 51, SJR: 3.048, h-index: 129)
Alternatives to the High Cost of Litigation     Hybrid Journal   (Followers: 3)
American Anthropologist     Hybrid Journal   (Followers: 152, SJR: 0.951, h-index: 61)
American Business Law J.     Hybrid Journal   (Followers: 24, SJR: 0.205, h-index: 17)
American Ethnologist     Hybrid Journal   (Followers: 93, SJR: 2.325, h-index: 51)
American J. of Economics and Sociology     Hybrid Journal   (Followers: 29, SJR: 0.211, h-index: 26)
American J. of Hematology     Hybrid Journal   (Followers: 35, SJR: 1.761, h-index: 77)
American J. of Human Biology     Hybrid Journal   (Followers: 13, SJR: 1.018, h-index: 58)
American J. of Industrial Medicine     Hybrid Journal   (Followers: 16, SJR: 0.993, h-index: 85)
American J. of Medical Genetics Part A     Hybrid Journal   (Followers: 16, SJR: 1.115, h-index: 61)
American J. of Medical Genetics Part B: Neuropsychiatric Genetics     Hybrid Journal   (Followers: 4, SJR: 1.771, h-index: 107)
American J. of Medical Genetics Part C: Seminars in Medical Genetics     Partially Free   (Followers: 6, SJR: 2.315, h-index: 79)
American J. of Physical Anthropology     Hybrid Journal   (Followers: 37, SJR: 1.41, h-index: 88)
American J. of Political Science     Hybrid Journal   (Followers: 290, SJR: 5.101, h-index: 114)
American J. of Primatology     Hybrid Journal   (Followers: 16, SJR: 1.197, h-index: 63)
American J. of Reproductive Immunology     Hybrid Journal   (Followers: 3, SJR: 1.347, h-index: 75)
American J. of Transplantation     Hybrid Journal   (Followers: 18, SJR: 2.792, h-index: 140)
American J. on Addictions     Hybrid Journal   (Followers: 9, SJR: 0.843, h-index: 57)
Anaesthesia     Hybrid Journal   (Followers: 138, SJR: 1.404, h-index: 88)
Analyses of Social Issues and Public Policy     Hybrid Journal   (Followers: 9, SJR: 0.397, h-index: 18)
Analytic Philosophy     Hybrid Journal   (Followers: 20)
Anatomia, Histologia, Embryologia: J. of Veterinary Medicine Series C     Hybrid Journal   (Followers: 3, SJR: 0.295, h-index: 27)
Anatomical Sciences Education     Hybrid Journal   (Followers: 1, SJR: 0.633, h-index: 24)
Andrologia     Hybrid Journal   (Followers: 2, SJR: 0.528, h-index: 45)
Andrology     Hybrid Journal   (Followers: 2, SJR: 0.979, h-index: 14)
Angewandte Chemie     Hybrid Journal   (Followers: 179)
Angewandte Chemie Intl. Edition     Hybrid Journal   (Followers: 229, SJR: 6.229, h-index: 397)
Animal Conservation     Hybrid Journal   (Followers: 41, SJR: 1.576, h-index: 62)
Animal Genetics     Hybrid Journal   (Followers: 8, SJR: 0.957, h-index: 67)
Animal Science J.     Hybrid Journal   (Followers: 6, SJR: 0.569, h-index: 24)
Annalen der Physik     Hybrid Journal   (Followers: 5, SJR: 1.46, h-index: 40)
Annals of Anthropological Practice     Partially Free   (Followers: 2, SJR: 0.187, h-index: 5)
Annals of Applied Biology     Hybrid Journal   (Followers: 7, SJR: 0.816, h-index: 56)
Annals of Clinical and Translational Neurology     Open Access   (Followers: 1)
Annals of Human Genetics     Hybrid Journal   (Followers: 9, SJR: 1.191, h-index: 67)
Annals of Neurology     Hybrid Journal   (Followers: 48, SJR: 5.584, h-index: 241)
Annals of Noninvasive Electrocardiology     Hybrid Journal   (Followers: 1, SJR: 0.531, h-index: 38)
Annals of Public and Cooperative Economics     Hybrid Journal   (Followers: 8, SJR: 0.336, h-index: 23)
Annals of the New York Academy of Sciences     Hybrid Journal   (Followers: 5, SJR: 2.389, h-index: 189)
Annual Bulletin of Historical Literature     Hybrid Journal   (Followers: 13)
Annual Review of Information Science and Technology     Hybrid Journal   (Followers: 14)
Anthropology & Education Quarterly     Hybrid Journal   (Followers: 25, SJR: 0.72, h-index: 31)
Anthropology & Humanism     Hybrid Journal   (Followers: 17, SJR: 0.137, h-index: 3)
Anthropology News     Hybrid Journal   (Followers: 15)
Anthropology of Consciousness     Hybrid Journal   (Followers: 11, SJR: 0.172, h-index: 5)
Anthropology of Work Review     Hybrid Journal   (Followers: 11, SJR: 0.256, h-index: 5)
Anthropology Today     Hybrid Journal   (Followers: 91, SJR: 0.545, h-index: 15)
Antipode     Hybrid Journal   (Followers: 50, SJR: 2.212, h-index: 69)
Anz J. of Surgery     Hybrid Journal   (Followers: 8, SJR: 0.432, h-index: 59)
Anzeiger für Schädlingskunde     Hybrid Journal   (Followers: 1)
Apmis     Hybrid Journal   (Followers: 1, SJR: 0.855, h-index: 73)
Applied Cognitive Psychology     Hybrid Journal   (Followers: 70, SJR: 0.754, h-index: 69)
Applied Organometallic Chemistry     Hybrid Journal   (Followers: 7, SJR: 0.632, h-index: 58)
Applied Psychology     Hybrid Journal   (Followers: 209, SJR: 1.023, h-index: 64)
Applied Psychology: Health and Well-Being     Hybrid Journal   (Followers: 50, SJR: 0.868, h-index: 13)
Applied Stochastic Models in Business and Industry     Hybrid Journal   (Followers: 5, SJR: 0.613, h-index: 24)
Aquaculture Nutrition     Hybrid Journal   (Followers: 14, SJR: 1.025, h-index: 55)
Aquaculture Research     Hybrid Journal   (Followers: 32, SJR: 0.807, h-index: 60)
Aquatic Conservation Marine and Freshwater Ecosystems     Hybrid Journal   (Followers: 36, SJR: 1.047, h-index: 57)
Arabian Archaeology and Epigraphy     Hybrid Journal   (Followers: 11, SJR: 0.453, h-index: 11)
Archaeological Prospection     Hybrid Journal   (Followers: 12, SJR: 0.922, h-index: 21)
Archaeology in Oceania     Hybrid Journal   (Followers: 13, SJR: 0.745, h-index: 18)
Archaeometry     Hybrid Journal   (Followers: 29, SJR: 0.809, h-index: 48)
Archeological Papers of The American Anthropological Association     Hybrid Journal   (Followers: 15, SJR: 0.156, h-index: 2)
Architectural Design     Hybrid Journal   (Followers: 26, SJR: 0.261, h-index: 9)
Archiv der Pharmazie     Hybrid Journal   (Followers: 3, SJR: 0.628, h-index: 43)
Archives of Drug Information     Hybrid Journal   (Followers: 5)
Archives of Insect Biochemistry and Physiology     Hybrid Journal   (SJR: 0.768, h-index: 54)
Area     Hybrid Journal   (Followers: 13, SJR: 0.938, h-index: 57)
Art History     Hybrid Journal   (Followers: 274, SJR: 0.153, h-index: 13)
Arthritis & Rheumatology     Hybrid Journal   (Followers: 54, SJR: 1.984, h-index: 20)
Arthritis Care & Research     Hybrid Journal   (Followers: 27, SJR: 2.256, h-index: 114)
Artificial Organs     Hybrid Journal   (Followers: 1, SJR: 0.872, h-index: 60)
ASHE Higher Education Reports     Hybrid Journal   (Followers: 15)
Asia & the Pacific Policy Studies     Open Access   (Followers: 16)
Asia Pacific J. of Human Resources     Hybrid Journal   (Followers: 326, SJR: 0.494, h-index: 19)
Asia Pacific Viewpoint     Hybrid Journal   (Followers: 1, SJR: 0.616, h-index: 26)
Asia-Pacific J. of Chemical Engineering     Hybrid Journal   (Followers: 8, SJR: 0.345, h-index: 20)
Asia-pacific J. of Clinical Oncology     Hybrid Journal   (Followers: 6, SJR: 0.554, h-index: 14)
Asia-Pacific J. of Financial Studies     Hybrid Journal   (SJR: 0.241, h-index: 7)
Asia-Pacific Psychiatry     Hybrid Journal   (Followers: 4, SJR: 0.377, h-index: 7)
Asian Economic J.     Hybrid Journal   (Followers: 8, SJR: 0.234, h-index: 21)
Asian Economic Policy Review     Hybrid Journal   (Followers: 4, SJR: 0.196, h-index: 12)
Asian J. of Control     Hybrid Journal   (SJR: 0.862, h-index: 34)
Asian J. of Endoscopic Surgery     Hybrid Journal   (Followers: 1, SJR: 0.394, h-index: 7)
Asian J. of Organic Chemistry     Hybrid Journal   (Followers: 6, SJR: 1.443, h-index: 19)
Asian J. of Social Psychology     Hybrid Journal   (Followers: 5, SJR: 0.665, h-index: 37)
Asian Politics and Policy     Hybrid Journal   (Followers: 12, SJR: 0.207, h-index: 7)
Asian Social Work and Policy Review     Hybrid Journal   (Followers: 5, SJR: 0.318, h-index: 5)
Asian-pacific Economic Literature     Hybrid Journal   (Followers: 5, SJR: 0.168, h-index: 15)
Assessment Update     Hybrid Journal   (Followers: 4)
Astronomische Nachrichten     Hybrid Journal   (Followers: 3, SJR: 0.701, h-index: 40)
Atmospheric Science Letters     Open Access   (Followers: 29, SJR: 1.332, h-index: 27)
Austral Ecology     Hybrid Journal   (Followers: 15, SJR: 1.095, h-index: 66)
Austral Entomology     Hybrid Journal   (Followers: 9, SJR: 0.524, h-index: 28)
Australasian J. of Dermatology     Hybrid Journal   (Followers: 8, SJR: 0.714, h-index: 40)
Australasian J. On Ageing     Hybrid Journal   (Followers: 6, SJR: 0.39, h-index: 22)
Australian & New Zealand J. of Statistics     Hybrid Journal   (Followers: 14, SJR: 0.275, h-index: 28)
Australian Accounting Review     Hybrid Journal   (Followers: 3, SJR: 0.709, h-index: 14)
Australian and New Zealand J. of Family Therapy (ANZJFT)     Hybrid Journal   (Followers: 3, SJR: 0.382, h-index: 12)
Australian and New Zealand J. of Obstetrics and Gynaecology     Hybrid Journal   (Followers: 47, SJR: 0.814, h-index: 49)
Australian and New Zealand J. of Public Health     Hybrid Journal   (Followers: 11, SJR: 0.82, h-index: 62)
Australian Dental J.     Hybrid Journal   (Followers: 6, SJR: 0.482, h-index: 46)
Australian Economic History Review     Hybrid Journal   (Followers: 6, SJR: 0.171, h-index: 12)
Australian Economic Papers     Hybrid Journal   (Followers: 31, SJR: 0.23, h-index: 9)
Australian Economic Review     Hybrid Journal   (Followers: 6, SJR: 0.357, h-index: 21)
Australian Endodontic J.     Hybrid Journal   (Followers: 3, SJR: 0.513, h-index: 24)
Australian J. of Agricultural and Resource Economics     Hybrid Journal   (Followers: 3, SJR: 0.765, h-index: 36)
Australian J. of Grape and Wine Research     Hybrid Journal   (Followers: 5, SJR: 0.879, h-index: 56)
Australian J. of Politics & History     Hybrid Journal   (Followers: 15, SJR: 0.203, h-index: 14)
Australian J. of Psychology     Hybrid Journal   (Followers: 18, SJR: 0.384, h-index: 30)
Australian J. of Public Administration     Hybrid Journal   (Followers: 419, SJR: 0.418, h-index: 29)
Australian J. of Rural Health     Hybrid Journal   (Followers: 5, SJR: 0.43, h-index: 34)
Australian Occupational Therapy J.     Hybrid Journal   (Followers: 72, SJR: 0.59, h-index: 29)
Australian Psychologist     Hybrid Journal   (Followers: 12, SJR: 0.331, h-index: 31)
Australian Veterinary J.     Hybrid Journal   (Followers: 23, SJR: 0.459, h-index: 45)
Autism Research     Hybrid Journal   (Followers: 36, SJR: 2.126, h-index: 39)
Autonomic & Autacoid Pharmacology     Hybrid Journal   (SJR: 0.371, h-index: 29)
Banks in Insurance Report     Hybrid Journal   (Followers: 1)
Basic & Clinical Pharmacology & Toxicology     Hybrid Journal   (Followers: 11, SJR: 0.539, h-index: 70)
Basic and Applied Pathology     Open Access   (Followers: 2, SJR: 0.113, h-index: 4)
Basin Research     Hybrid Journal   (Followers: 5, SJR: 1.54, h-index: 60)
Bauphysik     Hybrid Journal   (Followers: 2, SJR: 0.194, h-index: 5)
Bauregelliste A, Bauregelliste B Und Liste C     Hybrid Journal  
Bautechnik     Hybrid Journal   (Followers: 1, SJR: 0.321, h-index: 11)
Behavioral Interventions     Hybrid Journal   (Followers: 9, SJR: 0.297, h-index: 23)
Behavioral Sciences & the Law     Hybrid Journal   (Followers: 24, SJR: 0.736, h-index: 57)
Berichte Zur Wissenschaftsgeschichte     Hybrid Journal   (Followers: 10, SJR: 0.11, h-index: 5)
Beton- und Stahlbetonbau     Hybrid Journal   (Followers: 2, SJR: 0.493, h-index: 14)
Biochemistry and Molecular Biology Education     Hybrid Journal   (Followers: 6, SJR: 0.311, h-index: 26)
Bioelectromagnetics     Hybrid Journal   (Followers: 1, SJR: 0.568, h-index: 64)
Bioengineering & Translational Medicine     Open Access  
BioEssays     Hybrid Journal   (Followers: 10, SJR: 3.104, h-index: 155)
Bioethics     Hybrid Journal   (Followers: 14, SJR: 0.686, h-index: 39)
Biofuels, Bioproducts and Biorefining     Hybrid Journal   (Followers: 1, SJR: 1.725, h-index: 56)
Biological J. of the Linnean Society     Hybrid Journal   (Followers: 16, SJR: 1.172, h-index: 90)
Biological Reviews     Hybrid Journal   (Followers: 5, SJR: 6.469, h-index: 114)
Biologie in Unserer Zeit (Biuz)     Hybrid Journal   (Followers: 41, SJR: 0.12, h-index: 1)
Biology of the Cell     Full-text available via subscription   (Followers: 9, SJR: 1.812, h-index: 69)
Biomedical Chromatography     Hybrid Journal   (Followers: 6, SJR: 0.572, h-index: 49)
Biometrical J.     Hybrid Journal   (Followers: 5, SJR: 0.784, h-index: 44)
Biometrics     Hybrid Journal   (Followers: 37, SJR: 1.906, h-index: 96)
Biopharmaceutics and Drug Disposition     Hybrid Journal   (Followers: 10, SJR: 0.715, h-index: 44)
Biopolymers     Hybrid Journal   (Followers: 18, SJR: 1.199, h-index: 104)
Biotechnology and Applied Biochemistry     Hybrid Journal   (Followers: 44, SJR: 0.415, h-index: 55)
Biotechnology and Bioengineering     Hybrid Journal   (Followers: 152, SJR: 1.633, h-index: 146)
Biotechnology J.     Hybrid Journal   (Followers: 14, SJR: 1.185, h-index: 51)
Biotechnology Progress     Hybrid Journal   (Followers: 39, SJR: 0.736, h-index: 101)
Biotropica     Hybrid Journal   (Followers: 20, SJR: 1.374, h-index: 71)
Bipolar Disorders     Hybrid Journal   (Followers: 9, SJR: 2.592, h-index: 100)
Birth     Hybrid Journal   (Followers: 38, SJR: 0.763, h-index: 64)
Birth Defects Research Part A : Clinical and Molecular Teratology     Hybrid Journal   (Followers: 2, SJR: 0.727, h-index: 77)
Birth Defects Research Part B: Developmental and Reproductive Toxicology     Hybrid Journal   (Followers: 7, SJR: 0.468, h-index: 47)
Birth Defects Research Part C : Embryo Today : Reviews     Hybrid Journal   (SJR: 1.513, h-index: 55)
BJOG : An Intl. J. of Obstetrics and Gynaecology     Partially Free   (Followers: 247, SJR: 2.083, h-index: 125)

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Journal Cover Applied Stochastic Models in Business and Industry
  [SJR: 0.613]   [H-I: 24]   [5 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1524-1904 - ISSN (Online) 1526-4025
   Published by John Wiley and Sons Homepage  [1589 journals]
  • Estimation and application of semiparametric stochastic volatility models
           based on kernel density estimation and hidden Markov models
    • Authors: Hong-Xia Hao; Jin-Guan Lin, Xing-Fang Huang, Hong-Xia Wang, Yan-Yong Zhao
      Abstract: Discrete-time stochastic volatility models play a key role in the analysis of financial time series. However, the parametric assumption of conditional distribution for asset returns, given the volatility, has been questioned. When the conditional distribution is unknown and unspecified, in this paper, a maximum-likelihood estimation approach for the semiparametric stochastic volatility models is proposed based on kernel density estimation and hidden Markov models. Several numerical studies are conducted to evaluate the finite sample performance of the proposed estimation method. Implementation on empirical studies also illustrates the validity of the proposed method in practice.
      PubDate: 2018-01-19T03:52:27.189301-05:
      DOI: 10.1002/asmb.2305
       
  • Coherent system with standby components
    • Authors: Serkan Eryilmaz; T. Erman Erkan
      Abstract: A coherent system that consists of n independent components and equipped with r cold standby components is considered. A generalized mixture representation for the survival function of such a system is obtained, and it is used to examine reliability properties of the system. In particular, the effect of adding r standby components to a given set of original components is measured by computing mean time to failure of the system. The limiting behavior of the failure rate of the system is also examined using the mixture representation. The results are illustrated for a bridge system. A case study that is concerned with an oil pipeline system is also presented.
      PubDate: 2018-01-19T03:51:50.543501-05:
      DOI: 10.1002/asmb.2307
       
  • Special issue on Data Fusion
    • Authors: Daniel R. Jeske; Min-ge Xie
      PubDate: 2018-01-11T03:35:45.418819-05:
      DOI: 10.1002/asmb.2302
       
  • The empirical test on investment efficiency and influence of equity
           incentive in supply-side structural reform: Based on the two-tier
           stochastic frontier approach
    • Authors: Changqian Xie; Lun Li
      Abstract: This paper first empirically measured the investment efficiency and the influence of equity incentive on investment efficiency of listed companies in China within supply-side structural reform based on the two-tier stochastic frontier approach. The two-tier stochastic frontier model was combined with the traditional Richardson Model and the data of empirical test were based on the nonfinancial companies, which is listed on Shanghai and Shenzhen A-Share Markets in the period 2009 to 2015. On the aspect of investment efficiency, the different results were obtained from the overall empirical test, and further tests grouped by property rights, scales, and regions, and the corresponding reasons were analyzed. On the other aspect of influence of equity incentive on investment efficiency, the results showed that the implementation of equity incentive contributed to improve the overinvestment and underinvestment but the effects were not considerable in Chinese listed companies studied in this paper. Last, some suggestions on the problems found during the research were put forward.
      PubDate: 2018-01-11T03:30:35.902994-05:
      DOI: 10.1002/asmb.2304
       
  • Stochastic intrinsic Kriging for simulation metamodeling
    • Authors: Ehsan Mehdad; Jack P.C. Kleijnen
      Abstract: Kriging (or a Gaussian process) provides metamodels for deterministic and random simulation models. Actually, there are several types of Kriging; the classic type is the so-called universal Kriging, which includes ordinary Kriging. These classic types require estimation of the trend in the input-output data of the underlying simulation model; this estimation weakens the Kriging metamodel. We therefore consider the so-called intrinsic Kriging (IK), which originated in geostatistics, and derive IK types for deterministic simulations and random simulations, respectively. Moreover, for random simulations, we derive experimental designs that specify the number of replications that varies with the input combination of the simulation model. To compare the performance of IK and classic Kriging, we use several numerical experiments with deterministic simulations and random simulations, respectively. These experiments show that IK gives better metamodels, in most experiments.
      PubDate: 2018-01-03T04:27:35.774515-05:
      DOI: 10.1002/asmb.2300
       
  • Robust stochastic control modeling of dam discharge to suppress overgrowth
           of downstream harmful algae
    • Authors: Hidekazu Yoshioka; Yuta Yaegashi
      Abstract: The mathematical concept of multiplier robust control is applied to a dam operation problem, which is an urgent issue on river water environment, as a new industrial application of stochastic optimal control. The goal of the problem is to find a fit-for-purpose and environmentally sound operation policy of the flow discharge from a dam so that overgrowth of the harmful algae Cladophora glomerata Kützing in its downstream river is effectively suppressed. A minimal stochastic differential equation for the algae growth dynamics with uncertain growth rate is first presented. The performance index to be maximized by the operator of the dam while minimized by nature is formulated within the framework of differential games. The dynamic programming principle leads to a Hamilton-Jacobi-Bellman-Isaacs equation whose solution determines the worst-case optimal operation policy of the dam, ie, the policy that the operator wants to find. Application of the model to overgrowth suppression of Cladophora glomerata Kützing just downstream of a dam in a Japanese river is then carried out. Values of the model parameters are identified with which the model successfully reproduces the observed population dynamics. A series of numerical experiments are performed to find the most effective operation policy of the dam based on a relaxation of the current policy.
      PubDate: 2017-12-27T00:56:51.757129-05:
      DOI: 10.1002/asmb.2301
       
  • Imputation for multisource data with comparison and assessment techniques
    • Authors: Emily Casleton; Dave Osthus, Kendra Van Buren
      Abstract: Missing data are prevalent issue in analyses involving data collection. The problem of missing data is exacerbated for multisource analysis, where data from multiple sensors are combined to arrive at a single conclusion. In this scenario, it is more likely to occur and can lead to discarding a large amount of data collected; however, the information from observed sensors can be leveraged to estimate those values not observed. We propose two methods for imputation of multisource data, both of which take advantage of potential correlation between data from different sensors, through ridge regression and a state-space model. These methods, as well as the common median imputation, are applied to data collected from a variety of sensors monitoring an experimental facility. Performance of imputation methods is compared with the mean absolute deviation; however, rather than using this metric to solely rank the methods, we also propose an approach to identify significant differences. Imputation techniques will also be assessed by their ability to produce appropriate confidence intervals, through coverage and length, around the imputed values. Finally, performance of imputed datasets is compared with a marginalized dataset through a weighted k-means clustering. In general, we found that imputation through a dynamic linear model tended to be the most accurate and to produce the most precise confidence intervals, and that imputing the missing values and down weighting them with respect to observed values in the analysis led to the most accurate performance. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
      PubDate: 2017-12-27T00:40:54.874591-05:
      DOI: 10.1002/asmb.2299
       
  • A rule-based method of spike detection and suppression and its application
           in a control system for additive manufacturing
    • Authors: Wojciech Rafajłowicz; Ewaryst Rafajłowicz
      Abstract: We propose a rule-based method of spike detection and suppression method. This method is an extension of the jump detector that was proposed by the second author, M. Pawlak and A. Steland. Its elementary properties are established, and the example of application for a laser power control in a 3-dimensional additive manufacturing process is discussed.
      PubDate: 2017-12-05T04:31:39.064624-05:
      DOI: 10.1002/asmb.2298
       
  • Analysis of definitive screening designs: Screening vs prediction
    • Authors: Maria L. Weese; Philip J. Ramsey, Douglas C. Montgomery
      Abstract: The use of definitive screening designs (DSDs) has been increasing since their introduction in 2011. These designs are used to screen factors and to make predictions. We assert that the choice of analysis method for these designs depends on the goal of the experiment, screening, or prediction. In this work, we present simulation results to address the explanatory (screening) use and the predictive use of DSDs. To address the predictive ability of DSDs, we use two 5-factor DSDs and simultaneously run central composite designs case studies on which we will compare several common analysis methods. Overall, we find that for screening purposes, the Dantzig selector using the Bayesian Information Criterion statistic is a good analysis choice; however, when the goal of analysis is prediction forward selection using the Bayesian Information Criterion statistic produces models with a lower mean squared prediction error.
      PubDate: 2017-12-05T04:31:11.369287-05:
      DOI: 10.1002/asmb.2297
       
  • Planning accelerated life tests with random effects of test chambers
    • Authors: Kangwon Seo; Rong Pan
      Abstract: In accelerated life tests (ALTs), test units are often tested in multiple test chambers along with different stress conditions. The nonhomogeneity of test chambers precludes the complete randomized experiment and may affect the life-stress relationship of the test product. The chamber-to-chamber variation should be taken into account for ALT planning so as to obtain more accurate test results. In this paper, planning ALTs under a nested experimental design structure with random test chamber effects is studied. First, by a 2-phase approach, we illustrate to what extent different test chamber assignments to stress conditions may impact the estimation of unknown parameters. Then, D-optimal test plans with 2 test chambers are considered. To construct the optimal design, we establish the generalized linear mixed model for failure-time data and apply a quasi-likelihood method, where test chamber assignments, as well as other decision variables that are required for planning ALTs, are simultaneously determined.
      PubDate: 2017-12-05T04:26:36.240968-05:
      DOI: 10.1002/asmb.2296
       
  • Reliability modelling incorporating load share and frailty
    • Authors: G. Asha; A. Vincent Raja, Nalini Ravishanker
      Abstract: The stochastic behaviour of lifetimes of a two component system is often primarily influenced by the system structure and by the covariates shared by the components. Any meaningful attempt to model the lifetimes must take into consideration the factors affecting their stochastic behaviour. In particular, for a load share system, we describe a reliability model incorporating both the load share dependence and the effect of observed and unobserved covariates. The model includes a bivariate Weibull to characterize load share, a positive stable distribution to describe frailty, and also incorporates effects of observed covariates. We investigate various interesting reliability properties of this model using cross ratio functions and conditional survivor functions. We implement maximum likelihood estimation of the model parameters and discuss model adequacy and selection. We illustrate our approach using a simulation study. For a real data situation, we demonstrate the superiority of the proposed model that incorporates both load share and frailty effects over competing models that incorporate just one of these effects. An attractive and computationally simple cross-validation technique is introduced to reconfirm the claim. We conclude with a summary and discussion.
      PubDate: 2017-11-17T06:00:44.671136-05:
      DOI: 10.1002/asmb.2294
       
  • A dynamic fusion system for fast nuclear source detection and localization
           with mobile sensor networks
    • Authors: Aude Grelaud; Priyam Mitra, Minge Xie, Rong Chen
      Abstract: This paper proposes a dynamic system, with an associated fusion learning inference procedure, to perform real-time detection and localization of nuclear sources using a network of mobile sensors. This is motivated by the need for a reliable detection system in order to prevent nuclear attacks in major cities such as New York City. The approach advocated here installs a large number of relatively inexpensive (and perhaps relatively less accurate) nuclear source detection sensors and GPS devices in taxis and police vehicles moving in the city. Sensor readings and GPS information are sent to a control center at a high frequency, where the information is immediately processed and fused with the earlier signals. We develop a real-time detection and localization method aimed at detecting the presence of a nuclear source and estimating its location and power. We adopt a Bayesian framework to perform the fusion learning and use a sequential Monte Carlo algorithm to estimate the parameters of the model and to perform real-time localization. A simulation study is provided to assess the performance of the method for both stationary and moving sources. The results provide guidance and recommendations for an actual implementation of such a surveillance system. Copyright © 2017 John Wiley & Sons, Ltd.
      PubDate: 2017-11-17T06:00:36.364339-05:
      DOI: 10.1002/asmb.2293
       
  • Bounds for the reliability functions of coherent systems with
           heterogeneous components
    • Authors: Patryk Miziuła; Jorge Navarro
      Abstract: The computation of the reliability function of a (complex) coherent system is a difficult task. Hence, sometimes, we should simply work with some bounds (approximations). The computation of these bounds has been widely studied in the case of coherent systems with independent and identically distributed (IID) components. However, few results have been obtained in the case of heterogeneous (non ID) components. In this paper, we derive explicit bounds for systems with heterogeneous (independent or dependent) components. Also some stochastic comparisons are obtained. Some illustrative examples are included where we compare the different bounds proposed in the paper.
      PubDate: 2017-11-09T05:06:13.939942-05:
      DOI: 10.1002/asmb.2289
       
  • Practical arbitrage-free scenario tree reduction methods and their
           applications in financial optimization
    • Authors: Zhiping Chen; Zhe Yan
      Abstract: We construct an arbitrage-free scenario tree reduction model, from which some arbitrage-free scenario tree reduction algorithms are designed. They ensure that the reduced scenario trees are arbitrage free. Numerical results show the practicality and efficiency of the proposed algorithms. Results for multistage portfolio selection problems demonstrate the necessity and importance for guaranteeing that the reduced scenario trees are arbitrage free, as well as the practicality of the proposed arbitrage-free scenario tree reduction algorithms for financial optimization.
      PubDate: 2017-10-27T04:46:35.158726-05:
      DOI: 10.1002/asmb.2290
       
  • Estimation and status prediction in a discrete mover-stayer model with
           covariate effects on stayer's probability
    • Authors: Halina Frydman; Anna Matuszyk
      Abstract: A discrete-time mover-stayer (MS) model is an extension of a discrete-time Markov chain, which assumes a simple form of population heterogeneity. The individuals in the population are either stayers, who never leave their initial states or movers who move according to a Markov chain. We, in turn, propose an extension of the MS model by specifying the stayer's probability as a logistic function of an individual's covariates. Such extension has been recently discussed for a continuous time MS but has not been considered before for a discrete time one. This extension allows for an in-sample classification of subjects who never left their initial states into stayers or movers. The parameters of an extended MS model are estimated using the expectation-maximization algorithm. A novel bootstrap procedure is proposed for out of sample validation of the in-sample classification. The bootstrap procedure is also applied to validate the in-sample classification with respect to a more general dichotomy than the MS one. The developed methods are illustrated with the data set on installment loans. But they can be applied more broadly in credit risk area, where prediction of creditworthiness of a loan borrower or lessee is of major interest.
      PubDate: 2017-10-27T04:40:29.948077-05:
      DOI: 10.1002/asmb.2292
       
  • Inferring social structure from continuous-time interaction data
    • Authors: Wesley Lee; Bailey Fosdick, Tyler McCormick
      Abstract: Relational event data, which consist of events involving pairs of actors over time, are now commonly available at the finest of temporal resolutions. Existing continuous-time methods for modeling such data are based on point processes and directly model interaction “contagion,” whereby one interaction increases the propensity of future interactions among actors, often as dictated by some latent variable structure. In this article, we present an alternative approach to using temporal-relational point process models for continuous-time event data. We characterize interactions between a pair of actors as either spurious or as resulting from an underlying, persistent connection in a latent social network. We argue that consistent deviations from expected behavior, rather than solely high frequency counts, are crucial for identifying well-established underlying social relationships. This study aims to explore these latent network structures in two contexts: one comprising of college students and another involving barn swallows.
      PubDate: 2017-10-20T06:33:42.255857-05:
      DOI: 10.1002/asmb.2285
       
  • An index tracking model with stratified sampling and optimal allocation
    • Authors: Meihua Wang; Fengmin Xu, Yu-Hong Dai
      Abstract: This paper investigates the portfolio strategy problem for passive fund management. We propose a novel portfolio strategy that combines the existing stratified strategy and optimized sampling strategy. The proposed method enables one to include adequate practical information in portfolio decision making, and promotes better out-of-sample performance. A mixed-integer program model is built that captures the stratification information, the cardinality requirement, and other practical constraints. The corresponding model is able to forecast and generate optimal tracking portfolios with high performance, especially in out-of-sample time period. As mixed-integer program is a well-known NP-hard problem, to tackle the computational challenge, we propose a stratified hybrid genetic algorithm, in which a novel crossover operator is introduced. To evaluate the proposed strategy and algorithm, we conduct numerical tests on real data sets collected from China Stock Exchange Markets. The experimental results show that the algorithm runs efficiently and the portfolio strategy performs significantly better than other existing strategies.
      PubDate: 2017-10-16T02:35:28.833612-05:
      DOI: 10.1002/asmb.2287
       
  • A MCMC approach for modeling customer lifetime behavior using the
           COM-Poisson distribution
    • Authors: Mohamed Ben Mzoughia; Sharad Borle, Mohamed Limam
      Abstract: One of the major challenges associated with the measurement of customer lifetime value is selecting an appropriate model for predicting customer future transactions. Among such models, the Pareto/negative binomial distribution (Pareto/NBD) is the most prevalent in noncontractual relationships characterized by latent customer defections; ie, defections are not observed by the firm when they happen. However, this model and its applications have some shortcomings. Firstly, a methodological shortcoming is that the Pareto/NBD, like all lifetime transaction models based on statistical distributions, assumes that the number of transactions by a customer follows a Poisson distribution. However, many applications have an empirical distribution that does not fit a Poisson model. Secondly, a computational concern is that the implementation of Pareto/NBD model presents some estimation challenges specifically related to the numerous evaluation of the Gaussian hypergeometric function. Finally, the model provides 4 parameters as output, which is insufficient to link the individual purchasing behavior to socio-demographic information and to predict the behavior of new customers. In this paper, we model a customer's lifetime transactions using the Conway-Maxwell-Poisson distribution, which is a generalization of the Poisson distribution, offering more flexibility and a better fit to real-world discrete data. To estimate parameters, we propose a Markov chain Monte Carlo algorithm, which is easy to implement. Use of this Bayesian paradigm provides individual customer estimates, which help link purchase behavior to socio-demographic characteristics and an opportunity to target individual customers.
      PubDate: 2017-09-29T11:15:05.007395-05:
      DOI: 10.1002/asmb.2276
       
  • A beta partial least squares regression model: Diagnostics and application
           to mining industry data
    • Authors: Mauricio Huerta; Víctor Leiva, Camilo Lillo, Marcelo Rodríguez
      Abstract: We propose a methodology based on partial least squares (PLS) regression models using the beta distribution, which is useful for describing data measured between zero and one. The beta PLS model parameters are estimated with the maximum likelihood method, whereas a randomized quantile residual and the generalized Cook and Mahalanobis distances are considered as diagnostic methods. A simulation study is provided for evaluating the performance of these diagnostic methods. We illustrate the methodology with real-world mining data. The results obtained in this study based on the beta PLS model and its diagnostics may be of interest for the mining industry.
      PubDate: 2017-09-29T11:14:50.698196-05:
      DOI: 10.1002/asmb.2278
       
  • Some results on information properties of coherent systems
    • Authors: Abdolsaeed Toomaj; Antonio Di Crescenzo, Mahdi Doostparast
      Abstract: This paper considers information properties of coherent systems when component lifetimes are independent and identically distributed. Some results on the entropy of coherent systems in terms of ordering properties of component distributions are proposed. Moreover, various sufficient conditions are given under which the entropy order among systems as well as the corresponding dual systems hold. Specifically, it is proved that under some conditions, the entropy order among component lifetimes is preserved under coherent system formations. The findings are based on system signatures as a useful measure from comparison purposes. Furthermore, some results on the system's entropy are derived when lifetimes of components are dependent and identically distributed. Several illustrative examples are also given.
      PubDate: 2017-09-15T06:30:26.599466-05:
      DOI: 10.1002/asmb.2277
       
  • Control charts for monitoring correlated counts with a finite range
    • Authors: Athanasios C. Rakitzis; Christian H. Weiß, Philippe Castagliola
      Abstract: Correlated count data processes with a finite range can be adequately described by a first-order binomial autoregressive model. However, in several practical applications, these data demonstrate extra-binomial variation, and a more appropriate choice is the first-order beta-binomial autoregressive model. In this paper, we propose and study control charts that can be used for the monitoring of these 2 processes. Practical guidelines concerning their statistical design are provided, whereas the effect of the extra-binomial variation is investigated as well. Finally, the practical application of the proposed schemes is illustrated via a real-data example.
      PubDate: 2017-09-15T05:35:58.938467-05:
      DOI: 10.1002/asmb.2275
       
  • An evaluation of the multivariate dispersion charts with estimated
           parameters under non-normality
    • Authors: A. Mostajeran; N. Iranpanah, R. Noorossana
      Abstract: Various charts such as S , W, and G are used for monitoring process dispersion. Most of these charts are based on the normality assumption, while exact distribution of the control statistic is unknown, and thus limiting distribution of control statistic is employed which is applicable for large sample sizes. In practice, the normality assumption of distribution might be violated, while it is not always possible to collect large sample size. Furthermore, to use control charts in practice, the in-control state usually has to be estimated. Such estimation has a negative effect on the performance of control chart. Non-parametric bootstrap control charts can be considered as an alternative when the distribution is unknown or a collection of large sample size is not possible or the process parameters are estimated from a Phase I data set. In this paper, non-parametric bootstrap multivariate control charts S , W, and G are introduced, and their performances are compared against Shewhart-type control charts. The proposed method is based on bootstrapping the data used for estimating the in-control state. Simulation results show satisfactory performance for the bootstrap control charts. Ultimately, the proposed control charts are applied to a real case study.
      PubDate: 2017-08-31T06:07:13.163924-05:
      DOI: 10.1002/asmb.2272
       
  • Forecasting mortality rate by multivariate singular spectrum analysis
    • Authors: Rahim Mahmoudvand; Dimitrios Konstantinides, Paulo Canas Rodrigues
      Abstract: In this paper, we investigate the possibility of using multivariate singular spectrum analysis (SSA), a nonparametric technique in the field of time series analysis, for mortality forecasting. We consider a real data application with 9 European countries: Belgium, Denmark, Finland, France, Italy, Netherlands, Norway, Sweden, and Switzerland, over a period 1900 to 2009, and a simulation study based on the data set. The results show the superiority of multivariate SSA in comparison with the univariate SSA, in terms of forecasting accuracy.
      PubDate: 2017-08-25T05:36:03.401668-05:
      DOI: 10.1002/asmb.2274
       
  • Why indexing works
    • Authors: J. B. Heaton; N. G. Polson, J. H. Witte
      Abstract: We develop a simple stock selection model to explain why active equity managers tend to underperform a benchmark index. We motivate our model with the empirical observation that the best performing stocks in a broad market index often perform much better than the other stocks in the index. Randomly selecting a subset of securities from the index may dramatically increase the chance of underperforming the index. The relative likelihood of underperformance by investors choosing active management likely is much more important than the loss those same investors take due to the higher fees of active management relative to passive index investing. Thus, active management may be even more challenging than previously believed, and the stakes for finding the best active managers may be larger than previously assumed.
      PubDate: 2017-08-22T03:50:35.583666-05:
      DOI: 10.1002/asmb.2271
       
  • A nondisruptive reliability approach to assess the health of microseismic
           sensing networks
    • Authors: D. Neira; G. Soto, J. Fontbona, J. Prado, S. Gaete
      Abstract: Microseismic sensing networks are important tools for the assessment and control of geomechanical hazards in underground mining operations. In such a setting, the maintenance of a healthy network, that is, one that accurately registers all microseisms above some minimum energy level with acceptable levels of noise, is crucially relevant.In this paper, we develop a nondisruptive method to monitor the health of such a network, by associating with each sensor a set of performance indexes, inspired from reliability engineering, which are estimated from the set of registered signals. Our method addresses 2 relevant features of each of the sensors' behavior, namely, what type of noise is or might be affecting the registering process, and how effective at registering microseisms the sensor is.The method is evaluated through a case study with microseismic data registered at the Chilean underground mine El Teniente. This study illustrates our method's capability to discriminate and rank sensors with satisfactory, poor, or defective sensing performances, as well as to characterize their failure profile or type, an information that can be used to plan or optimize the network maintenance procedures.
      PubDate: 2017-08-15T03:25:31.158176-05:
      DOI: 10.1002/asmb.2266
       
  • Risk assessment of failure of rock bolts in underground coal mines using
           support vector machines
    • Authors: Peng Jiang; Peter Craig, Alan Crosky, Mojtaba Maghrebi, Ismet Canbulat, Serkan Saydam
      Abstract: In recent years, there has been an increasing incidence of failure of rock bolts due to stress corrosion cracking and localized corrosion attack in Australian underground coal mines. Unfortunately, prediction of the risk of failure from results obtained from laboratory testing is not necessarily reliable because it is difficult to properly simulate the mine environment. An alternative way of predicting failure is to apply machine learning methods to data obtained from underground mines. In this paper, support vector machines are built to predict failure of bolts in complex mine environments. Feature transformation and feature selection methods are applied to extract useful information from the original data. A dataset, which had continuous features and spatial data, was used to test the proposed model. The results showed that principal component analysis-based feature transformation provides reliable risk prediction.
      PubDate: 2017-08-15T03:10:43.829851-05:
      DOI: 10.1002/asmb.2273
       
  • The Pathmox approach for PLS path modeling: Discovering which constructs
           differentiate segments
    • Authors: Giuseppe Lamberti; Tomas Banet Aluja, Gaston Sanchez
      Abstract: The problem of heterogeneity represents a very important issue in the decision-making process. Furthermore, it has become common practice in the context of marketing research to assume that different population parameters are possible depending on sociodemographic and psycho-demographic variables such as age, gender, and social status. In recent decades, numerous approaches have been proposed with the aim of involving heterogeneity in the parameter estimation procedures. In partial least squares path modeling, the common practice consists of achieving a global measurement of the differences arising from heterogeneity. This leaves the analyst with the important task of detecting, a posteriori, which are the causal relationships (ie, path coefficients) that produce changes in the model. This is the case in Pathmox analysis, which solves the heterogeneity problem by building a binary tree to detect those segments of population that cause the heterogeneity. In this article, we propose extending the same Pathmox methodology to asses which particular endogenous equation of the structural model and which path coefficients are responsible of the difference.
      PubDate: 2017-08-11T04:46:22.851701-05:
      DOI: 10.1002/asmb.2270
       
  • Correlated model fusion
    • Authors: Andrew Hoegh; Scotland Leman
      Abstract: Model fusion methods, or more generally ensemble methods, are a useful tool for prediction. Combining predictions from a set of models smooths out biases and reduces variances of predictions from individual models, and hence, the combined predictions typically outperform those from individual models. In many algorithms, individual predictions are arithmetically averaged with equal weights. However, in the presence of correlated models, the fusion process is required to account for association between models; otherwise, the naively averaged predictions will be suboptimal. This article describes optimal model fusion principles and illustrates the potential pitfalls of naive fusion in the presence of correlated models for binary data. An efficient algorithm for correlated model fusion is detailed and applied to algorithms mining social media information to predict civil unrest. Copyright © 2017 John Wiley & Sons, Ltd.
      PubDate: 2017-08-04T06:20:37.693386-05:
      DOI: 10.1002/asmb.2261
       
  • A marginal contribution coefficient for sequences of nonstationary
           continuous Markov chains
    • Authors: Sílvio Alves Souza; Denise Duarte, Eduardo M. A. M. Mendes
      Abstract: In this work, a set of sequences of information (time series), under nonstationary regime, with continuous space state, discrete time, and a Markovian dependence, is considered. A new model that expresses the marginal transition density function of one sequence as a linear combination of the marginal transition density functions of all sequences in the set is proposed. The coefficients of this combination are denominated marginal contribution coefficients and represent how much each transition density function contributes to the calculation of a chosen transition density function. The proposed coefficient is a marginal coefficient because it can be computed instantaneously, and it may change from one time to another time since all calculations are performed before stationarity is reached. This clearly differentiates the new coefficient from well-known measures such as the cross-correlation and the coherence. The idea behind the model is that if a specific sequence has a high marginal contribution for the transition density function from another sequence, the first may be replaced by the latter without losing much information that means that the knowledge of few densities should be enough to recover the overall behaviour. Simulations, considering 2 chains, are presented so as to check the sensitivity of the proposed model. The methodology is also applied to a real data originated from a wire-drawing machine whose main function is to decrease the transverse diameter of metal wires. The behaviour of the level of acceleration of each bearing in relation to the other ones is then verified.
      PubDate: 2017-08-01T23:01:25.525366-05:
      DOI: 10.1002/asmb.2262
       
  • Effects of risk aversion and decision preference on equilibriums in supply
           chain finance incorporating bank credit with credit guarantee
    • Authors: Nina Yan; Chongqing Liu, Ye Liu, Baowen Sun
      Abstract: We constructed a Stackelberg game in a supply chain finance (SCF) system including a manufacturer, a capital-constrained retailer, and a bank that provides loans on the basis of the manufacturer's credit guarantee. To emphasize the financial service providers' risks, we assumed that both the bank and the manufacturer are risk-averse and formulated trade-off objective functions for both of them as the convex combination of the expected profit and conditional value-at-risk. To explore the effects of the risk preferences and decision preferences on SCF equilibriums, we mathematically analyzed the optimal order quantities, wholesale prices, and interest rates under different risk preference scenarios and performed numerical analyses to quantify the effects. We found that incorporating bank credit with a credit guarantee can effectively balance the retailer's financing risk between the bank and the manufacturer through interest rate charging and wholesale pricing. Moreover, SCF equilibriums with risk aversion are highly affected by the degree of both the lender's and guarantor's risk tolerance in regard to the borrower's default probability and will be more conservative than those in the risk-neutral cases that only maximize expected profit.
      PubDate: 2017-07-27T02:30:38.598256-05:
      DOI: 10.1002/asmb.2264
       
  • The choice of screening design
    • Authors: John Tyssedal; Muhammad Azam Chaudhry
      Abstract: A screening design is an experimental plan used for identifying the expectedly few active factors from potentially many. In this paper, we compare the performances of 3 experimental plans, a Plackett-Burman design, a minimum run resolution IV design, and a definitive screening design, all with 12 and 13 runs, when they are used for screening and 3 out of 6 factors are active. The functional relationship between the response and the factors was allowed to be of 2 types, a second-order model and a model with all main effects and interactions included. D-efficiencies for the designs ability to estimate parameters in such models were computed, but it turned out that these are not very informative for comparing the screening performances of the 2-level designs to the definitive screening design. The overall screening performance of the 2-level designs was quite good, but there exist situations where the definitive screening design, allowing both screening and estimation of second-order models in the same operation, has a reasonable high probability of being successful.
      PubDate: 2017-07-27T02:20:24.213014-05:
      DOI: 10.1002/asmb.2269
       
  • Stochastic optimization of an urban rail timetable under time-dependent
           and uncertain demand
    • Authors: Masoud Shakibayifar; Erfan Hassannayebi, Hossein Jafary, Arman Sajedinejad
      Abstract: Urban rail planning is extremely complex, mainly because it is a decision problem under different uncertainties. In practice, travel demand is generally uncertain, and therefore, the timetabling decisions must be based on accurate estimation. This research addresses the optimization of train timetable at public transit terminals of an urban rail in a stochastic setting. To cope with stochastic fluctuation of arrival rates, a two-stage stochastic programming model is developed. The objective is to construct a daily train schedule that minimizes the expected waiting time of passengers. Due to the high computational cost of evaluating the expected value objective, the sample average approximation method is applied. The method provided statistical estimations of the optimality gap as well as lower and upper bounds and the associated confidence intervals. Numerical experiments are performed to evaluate the performance of the proposed model and the solution method.
      PubDate: 2017-07-20T03:40:45.856594-05:
      DOI: 10.1002/asmb.2268
       
  • Phase II monitoring of changes in mean from high-dimensional data
    • Authors: Johan Lim; Sungim Lee
      Abstract: The generalized T2 chart (GT-chart), which is composed of the T2 statistic based on a small number of principal components and the remaining components, is a popular alternative to the traditional Hotelling's T2 control chart. However, the application of the GT-chart to high-dimensional data, which are now ubiquitous, encounters difficulties from high dimensionality similar to other multivariate procedures. The sample principal components and their eigenvalues do not consistently estimate the population values, and the GT-chart relying on them is also inconsistent in estimating the control limits. In this paper, we investigate the effects of high dimensionality on the GT-chart and then propose a corrected GT-chart using the recent results of random matrix theory for the spiked covariance model. We numerically show that the corrected GT-chart exhibits superior performance compared to the existing methods, including the GT-chart and Hotelling's T2 control chart, under various high-dimensional cases. Finally, we apply the proposed corrected GT-chart to monitor chemical processes introduced in the literature.
      PubDate: 2017-07-16T23:30:31.640334-05:
      DOI: 10.1002/asmb.2267
       
  • Sequential Bayesian learning for stochastic volatility with variance-gamma
           jumps in returns
    • Authors: Samir P. Warty; Hedibert F. Lopes, Nicholas G. Polson
      Abstract: In this work, we investigate sequential Bayesian estimation for inference of stochastic volatility with variance-gamma (SVVG) jumps in returns. We develop an estimation algorithm that combines the sequential learning auxiliary particle filter with the particle learning filter. Simulation evidence and empirical estimation results indicate that this approach is able to filter latent variances, identify latent jumps in returns, and provide sequential learning about the static parameters of SVVG. We demonstrate comparative performance of the sequential algorithm and off-line Markov Chain Monte Carlo in synthetic and real data applications.
      PubDate: 2017-06-21T03:26:48.533604-05:
      DOI: 10.1002/asmb.2258
       
  • Two stochastic dominance criteria based on tail comparisons
    • Authors: Julio Mulero; Miguel A. Sordo, Marilia C. de Souza, Alfonso Suárez-LLorens
      Abstract: Actuarial risks and financial asset returns are typically heavy tailed. In this paper, we introduce 2 stochastic dominance criteria, called the right-tail order and the left-tail order, to compare these variables stochastically. The criteria are based on comparisons of expected utilities, for 2 classes of utility functions that give more weight to the right or the left tail (depending on the context) of the distributions. We study their properties, applications, and connections with other classical criteria, including the increasing convex and the second-order stochastic dominance. Finally, we rank some parametric families of distributions and provide empirical evidence of the new stochastic dominance criteria with an example using real data.
      PubDate: 2017-06-19T00:21:00.010155-05:
      DOI: 10.1002/asmb.2260
       
  • Some closed form robust moment-based estimators for the MEM(1,1)
    • Authors: Wanbo Lu; Rui Ke
      Abstract: In this paper, we extend the closed form moment estimator (ordinary MCFE) for the autoregressive conditional duration model given by Lu et al (2016) and propose some closed form robust moment-based estimators for the multiplicative error model to deal with the additive and innovational outliers. The robustification of the closed form estimator is done by replacing the sample mean and sample autocorrelation with some robust estimators. These estimators are more robust than the quasi-maximum likelihood estimator (QMLE) often used to estimate this model, and they are easy to implement and do not require the use of any numerical optimization procedure and the choice of initial value. The performance of our proposal in estimating the parameters and forecasting conditional mean μt of the MEM(1,1) process is compared with the proposals existing in the literature via Monte Carlo experiments, and the results of these experiments show that our proposal outperforms the ordinary MCFE, QMLE, and least absolute deviation estimator in the presence of outliers in general. Finally, we fit the price durations of IBM stock with the robust closed form estimators and the benchmarks and analyze their performances in estimating model parameters and forecasting the irregularly spaced intraday Value at Risk.
      PubDate: 2017-06-19T00:16:35.174062-05:
      DOI: 10.1002/asmb.2259
       
  • Combining binomial test data via two-stage solutions
    • Authors: Janet Myhre; Daniel R. Jeske, Jun Li, Anne M. Hansen
      Abstract: A commonly occurring problem in reliability testing is how to combine pass/fail test data that is collected from disparate environments. We have worked with colleagues in aerospace engineering for a number of years where two types of test environments in use are ground tests and flight tests. Ground tests are less expensive and consequently more numerous. Flight tests are much less frequent, but directly reflect the actual usage environment. We discuss a relatively simple combining approach that realizes the benefit of a larger sample size by using ground test data, but at the same time accounts for the difference between the two environments. We compare our solution with what look like more sophisticated approaches to the problem in order to calibrate its limitations. Overall, we find that our proposed solution is robust to its inherent assumptions, which explains its usefulness in practice. Copyright © 2017 John Wiley & Sons, Ltd.
      PubDate: 2017-05-12T00:23:45.008786-05:
      DOI: 10.1002/asmb.2255
       
  • Multi-stage multivariate modeling of temporal patterns in prescription
           counts for competing drugs in a therapeutic category
    • Authors: Volodymyr Serhiyenko; Nalini Ravishanker, Rajkumar Venkatesan
      Abstract: This article describes statistical analyses pertaining to marketing data from a large multinational pharmaceutical firm. We describe models for monthly new prescription counts that are written by physicians for the firm's focal drug and for competing drugs, as functions of physician-specific and time-varying predictors. Modeling patterns in discrete-valued time series, and specifically time series of counts, based on large datasets, is the focus of much recent research attention. We first provide a brief overview of Bayesian approaches we have employed for modeling multivariate count time series using Markov Chain Monte Carlo methods. We then discuss a flexible level correlated model framework, which enables us to combine different marginal count distributions and to build a hierarchical model for the vector time series of counts, while accounting for the association among the components of the response vector, as well as possible overdispersion. We employ the integrated nested Laplace approximation (INLA) for fast approximate Bayesian modeling using the R-INLA package (r-inla.org). To enhance computational speed, we first build a model for each physician, use features of the estimated trends in the time-varying parameters in order to cluster the physicians into groups, and fit aggregate models for all physicians within each cluster. Our three-stage analysis can provide useful guidance to the pharmaceutical firm on their marketing actions. Copyright © 2017 John Wiley & Sons, Ltd.
      PubDate: 2017-02-17T01:56:52.271792-05:
      DOI: 10.1002/asmb.2232
       
  • Issue Information
    • Pages: 557 - 558
      Abstract: No abstract is available for this article.
      PubDate: 2017-12-08T00:34:18.702508-05:
      DOI: 10.1002/asmb.2199
       
 
 
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