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  Subjects -> MATHEMATICS (Total: 978 journals)
    - APPLIED MATHEMATICS (81 journals)
    - GEOMETRY AND TOPOLOGY (20 journals)
    - MATHEMATICS (723 journals)
    - MATHEMATICS (GENERAL) (41 journals)
    - NUMERICAL ANALYSIS (22 journals)
    - PROBABILITIES AND MATH STATISTICS (91 journals)

MATHEMATICS (723 journals)                  1 2 3 4 | Last

Showing 1 - 200 of 538 Journals sorted alphabetically
Abakós     Open Access   (Followers: 4)
Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg     Hybrid Journal   (Followers: 4)
Academic Voices : A Multidisciplinary Journal     Open Access   (Followers: 2)
Accounting Perspectives     Full-text available via subscription   (Followers: 7)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Mathematical Software (TOMS)     Hybrid Journal   (Followers: 6)
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 32)
Acta Applicandae Mathematicae     Hybrid Journal   (Followers: 1)
Acta Mathematica     Hybrid Journal   (Followers: 12)
Acta Mathematica Hungarica     Hybrid Journal   (Followers: 2)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5)
Acta Mathematica Sinica, English Series     Hybrid Journal   (Followers: 6)
Acta Mathematica Vietnamica     Hybrid Journal  
Acta Mathematicae Applicatae Sinica, English Series     Hybrid Journal  
Advanced Science Letters     Full-text available via subscription   (Followers: 10)
Advances in Applied Clifford Algebras     Hybrid Journal   (Followers: 4)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 4)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Decision Sciences     Open Access   (Followers: 3)
Advances in Difference Equations     Open Access   (Followers: 3)
Advances in Fixed Point Theory     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 14)
Advances in Linear Algebra & Matrix Theory     Open Access   (Followers: 3)
Advances in Materials Science     Open Access   (Followers: 14)
Advances in Mathematical Physics     Open Access   (Followers: 4)
Advances in Mathematics     Full-text available via subscription   (Followers: 11)
Advances in Nonlinear Analysis     Hybrid Journal  
Advances in Numerical Analysis     Open Access   (Followers: 5)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Pure and Applied Mathematics     Hybrid Journal   (Followers: 6)
Advances in Pure Mathematics     Open Access   (Followers: 6)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aequationes Mathematicae     Hybrid Journal   (Followers: 2)
African Journal of Educational Studies in Mathematics and Sciences     Full-text available via subscription   (Followers: 5)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Afrika Matematika     Hybrid Journal   (Followers: 1)
Air, Soil & Water Research     Open Access   (Followers: 12)
AKSIOMA Journal of Mathematics Education     Open Access   (Followers: 1)
Al-Jabar : Jurnal Pendidikan Matematika     Open Access   (Followers: 1)
Algebra and Logic     Hybrid Journal   (Followers: 6)
Algebra Colloquium     Hybrid Journal   (Followers: 4)
Algebra Universalis     Hybrid Journal   (Followers: 2)
Algorithmic Operations Research     Full-text available via subscription   (Followers: 5)
Algorithms     Open Access   (Followers: 11)
Algorithms Research     Open Access   (Followers: 1)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Mathematical Analysis     Open Access  
American Journal of Mathematics     Full-text available via subscription   (Followers: 6)
American Journal of Operations Research     Open Access   (Followers: 5)
An International Journal of Optimization and Control: Theories & Applications     Open Access   (Followers: 9)
Analele Universitatii Ovidius Constanta - Seria Matematica     Open Access   (Followers: 1)
Analysis and Applications     Hybrid Journal   (Followers: 1)
Analysis and Mathematical Physics     Hybrid Journal   (Followers: 5)
Analysis Mathematica     Full-text available via subscription  
Analysis. International mathematical journal of analysis and its applications     Hybrid Journal   (Followers: 2)
Annales Mathematicae Silesianae     Open Access  
Annales mathématiques du Québec     Hybrid Journal   (Followers: 4)
Annales Universitatis Paedagogicae Cracoviensis. Studia Mathematica     Open Access  
Annali di Matematica Pura ed Applicata     Hybrid Journal   (Followers: 1)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Discrete Mathematics     Full-text available via subscription   (Followers: 6)
Annals of Mathematics     Full-text available via subscription   (Followers: 1)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 13)
Annals of Pure and Applied Logic     Open Access   (Followers: 3)
Annals of the Alexandru Ioan Cuza University - Mathematics     Open Access  
Annals of the Institute of Statistical Mathematics     Hybrid Journal   (Followers: 1)
Annals of West University of Timisoara - Mathematics     Open Access  
Annuaire du Collège de France     Open Access   (Followers: 5)
ANZIAM Journal     Open Access   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applications of Mathematics     Hybrid Journal   (Followers: 2)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 13)
Applied Mathematics     Open Access   (Followers: 3)
Applied Mathematics     Open Access   (Followers: 7)
Applied Mathematics & Optimization     Hybrid Journal   (Followers: 9)
Applied Mathematics - A Journal of Chinese Universities     Hybrid Journal  
Applied Mathematics Letters     Full-text available via subscription   (Followers: 2)
Applied Mathematics Research eXpress     Hybrid Journal   (Followers: 1)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Arab Journal of Mathematical Sciences     Open Access   (Followers: 3)
Arabian Journal of Mathematics     Open Access   (Followers: 2)
Archive for Mathematical Logic     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
Armenian Journal of Mathematics     Open Access  
Arnold Mathematical Journal     Hybrid Journal   (Followers: 1)
Artificial Satellites     Open Access   (Followers: 21)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asian Journal of Algebra     Open Access   (Followers: 1)
Asian Journal of Current Engineering & Maths     Open Access  
Asian-European Journal of Mathematics     Hybrid Journal   (Followers: 2)
Australian Mathematics Teacher, The     Full-text available via subscription   (Followers: 6)
Australian Primary Mathematics Classroom     Full-text available via subscription   (Followers: 4)
Australian Senior Mathematics Journal     Full-text available via subscription   (Followers: 1)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Axioms     Open Access   (Followers: 1)
Baltic International Yearbook of Cognition, Logic and Communication     Open Access   (Followers: 1)
Basin Research     Hybrid Journal   (Followers: 5)
BIBECHANA     Open Access   (Followers: 2)
Biomath     Open Access  
BIT Numerical Mathematics     Hybrid Journal  
BoEM - Boletim online de Educação Matemática     Open Access  
Boletim Cearense de Educação e História da Matemática     Open Access  
Boletim de Educação Matemática     Open Access  
Boletín de la Sociedad Matemática Mexicana     Hybrid Journal  
Bollettino dell'Unione Matematica Italiana     Full-text available via subscription   (Followers: 1)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 20)
Bruno Pini Mathematical Analysis Seminar     Open Access  
Buletinul Academiei de Stiinte a Republicii Moldova. Matematica     Open Access   (Followers: 12)
Bulletin des Sciences Mathamatiques     Full-text available via subscription   (Followers: 4)
Bulletin of Dnipropetrovsk University. Series : Communications in Mathematical Modeling and Differential Equations Theory     Open Access   (Followers: 1)
Bulletin of Mathematical Sciences     Open Access   (Followers: 1)
Bulletin of Symbolic Logic     Full-text available via subscription   (Followers: 2)
Bulletin of the Australian Mathematical Society     Full-text available via subscription   (Followers: 1)
Bulletin of the Brazilian Mathematical Society, New Series     Hybrid Journal  
Bulletin of the London Mathematical Society     Hybrid Journal   (Followers: 4)
Bulletin of the Malaysian Mathematical Sciences Society     Hybrid Journal  
Calculus of Variations and Partial Differential Equations     Hybrid Journal  
Canadian Journal of Science, Mathematics and Technology Education     Hybrid Journal   (Followers: 19)
Carpathian Mathematical Publications     Open Access   (Followers: 1)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
CHANCE     Hybrid Journal   (Followers: 5)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
ChemSusChem     Hybrid Journal   (Followers: 7)
Chinese Annals of Mathematics, Series B     Hybrid Journal  
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Mathematics     Open Access  
Clean Air Journal     Full-text available via subscription   (Followers: 1)
Cogent Mathematics     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Collectanea Mathematica     Hybrid Journal  
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Commentarii Mathematici Helvetici     Hybrid Journal   (Followers: 1)
Communications in Combinatorics and Optimization     Open Access  
Communications in Contemporary Mathematics     Hybrid Journal  
Communications in Mathematical Physics     Hybrid Journal   (Followers: 2)
Communications On Pure & Applied Mathematics     Hybrid Journal   (Followers: 3)
Complex Analysis and its Synergies     Open Access   (Followers: 2)
Complex Variables and Elliptic Equations: An International Journal     Hybrid Journal  
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Compositio Mathematica     Full-text available via subscription   (Followers: 1)
Comptes Rendus Mathematique     Full-text available via subscription   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 3)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Optimization and Applications     Hybrid Journal   (Followers: 8)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 8)
Concrete Operators     Open Access   (Followers: 5)
Confluentes Mathematici     Hybrid Journal  
Contributions to Game Theory and Management     Open Access  
COSMOS     Hybrid Journal  
Cryptography and Communications     Hybrid Journal   (Followers: 13)
Cuadernos de Investigación y Formación en Educación Matemática     Open Access  
Cubo. A Mathematical Journal     Open Access  
Current Research in Biostatistics     Open Access   (Followers: 9)
Czechoslovak Mathematical Journal     Hybrid Journal   (Followers: 1)
Demographic Research     Open Access   (Followers: 11)
Demonstratio Mathematica     Open Access  
Dependence Modeling     Open Access  
Design Journal : An International Journal for All Aspects of Design     Hybrid Journal   (Followers: 30)
Developments in Clay Science     Full-text available via subscription   (Followers: 1)
Developments in Mineral Processing     Full-text available via subscription   (Followers: 3)
Dhaka University Journal of Science     Open Access  
Differential Equations and Dynamical Systems     Hybrid Journal   (Followers: 3)
Differentsial'nye Uravneniya     Open Access  
Discrete Mathematics     Hybrid Journal   (Followers: 8)
Discrete Mathematics & Theoretical Computer Science     Open Access  
Discrete Mathematics, Algorithms and Applications     Hybrid Journal   (Followers: 2)
Discussiones Mathematicae - General Algebra and Applications     Open Access  
Discussiones Mathematicae Graph Theory     Open Access   (Followers: 1)
Diskretnaya Matematika     Full-text available via subscription  
Dnipropetrovsk University Mathematics Bulletin     Open Access  
Doklady Akademii Nauk     Open Access  
Doklady Mathematics     Hybrid Journal  
Duke Mathematical Journal     Full-text available via subscription   (Followers: 1)
Eco Matemático     Open Access  
Econometrics     Open Access  
Edited Series on Advances in Nonlinear Science and Complexity     Full-text available via subscription  
Electronic Journal of Combinatorics     Open Access  
Electronic Journal of Differential Equations     Open Access  
Electronic Journal of Graph Theory and Applications     Open Access   (Followers: 2)
Electronic Notes in Discrete Mathematics     Full-text available via subscription   (Followers: 2)

        1 2 3 4 | Last

Journal Cover
Annals of Data Science
Number of Followers: 12  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2198-5804 - ISSN (Online) 2198-5812
Published by Springer-Verlag Homepage  [2351 journals]
  • Collective Anomaly Detection Techniques for Network Traffic Analysis
    • Authors: Mohiuddin Ahmed
      Pages: 497 - 512
      Abstract: In certain cyber-attack scenarios, such as flooding denial of service attacks, the data distribution changes significantly. This forms a collective anomaly, where some similar kinds of normal data instances appear in abnormally large numbers. Since they are not rare anomalies, existing anomaly detection techniques cannot properly identify them. This paper investigates detecting this behaviour using the existing clustering and co-clustering based techniques and utilizes the network traffic modelling technique via Hurst parameter to propose a more effective algorithm combining clustering and Hurst parameter. Experimental analysis reflects that the proposed Hurst parameter-based technique outperforms existing collective and rare anomaly detection techniques in terms of detection accuracy and false positive rates. The experimental results are based on benchmark datasets such as KDD Cup 1999 and UNSW-NB15 datasets.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0149-0
      Issue No: Vol. 5, No. 4 (2018)
       
  • Assessing Survival Time of Women with Cervical Cancer Using Various
           Parametric Frailty Models: A Case Study at Tikur Anbessa Specialized
           Hospital, Addis Ababa, Ethiopia
    • Authors: Selamawit Endale Gurmu
      Pages: 513 - 527
      Abstract: Cervical cancer is one of the leading causes of death in the world and represents a tremendous burden on patients, families and societies. It is estimated that over one million women worldwide currently have cervical cancer; most of them have not been diagnosed or have no access to treatment that could cure them or prolong their lives. The goal of this study is to investigate potential risk factors affecting survival time of women with cervical cancer at Tikur Anbessa specialized hospital. Data were taken from patients’ medical record card that enrolled during September 2011–September 2015. Kaplan–Meier estimation method, Cox proportional hazard model and parametric shared frailty model were used to analysis survival time of cervical cancer patients. Study subjects (cervical cancer patients) in this study came from clustered community and hence clustered survival data correlated at the regional level. Parametric frailty models will be explored assuming that women with in the same cluster (region for this study) shares similar risk factors. We used Exponential, Weibull, Log logistics and Log normal distributions and based on AIC criteria, all models were compared for their performance. The lognormal inverse Gaussian model has the minimum AIC value among the models compared. The results implied that not giving birth up to the study ends and married after twenty years were significantly prolong the survival time of patients while age class 51–60, 61–70, > 70, smoking cigarettes, patients with stage III and IV disease, family history of cervical cancer, history of abortion and living with HIV AIDS were significantly shorten survival time of patients. The findings of this study suggested that age, smoking cigarettes, stage, family history, abortion history, living with HIV AIDS, age at first marriage and age at first birth were major factors to survival time of patients. Heterogeneity between the regions in the survival time of cervical cancer patients, indicating that one needs to account for this clustering variable using frailty models. The fit statistics showed that lognormal inverse-Gaussian frailty model described the survival time of cervical cancer patients dataset better than other distributions used in this study.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0150-7
      Issue No: Vol. 5, No. 4 (2018)
       
  • Forecasting the Volatility of Ethiopian Birr/Euro Exchange Rate Using
           Garch-Type Models
    • Authors: Desa Daba Fufa; Belianeh Legesse Zeleke
      Pages: 529 - 547
      Abstract: This paper provides a robust analysis of volatility forecasting of Euro-ETB exchange rate using weekly data spanning the period January 3, 2000–December 2, 2015. The forecasting performance of various GARCH-type models is investigated based on forecasting performance criteria such as MSE and MAE based tests, and alternative measures of realized volatility. To our knowledge, this is the first study that focuses on Euro-ETB exchange rate using high frequency data, and a range of econometric models and forecast performance criteria. The empirical results indicate that the Euro-ETB exchange rate series exhibits persistent volatility clustering over the study period. We document evidence that ARCH (8), GARCH (1, 1), EGARCH (1, 1) and GJR-GARCH (2, 2) models with normal distribution, student’s-t distribution and GED are the best in-sample estimation models in terms of the volatility behavior of the series. Amongst these models, GJR-GARCH (2, 2) and GARCH (1, 1) with students t-distribution are found to perform best in terms of one step-ahead forecasting based on realized volatility calculated from the underlying daily data and squared weekly first differenced of the logarithm of the series, respectively. A one-step-ahead forecasted conditional variance of weekly Euro-ETB exchange rate portrays large spikes around 2010 and it is evident that weekly Euro-ETB exchange rate are volatile. This large spikes indicates that devaluation of Ethiopian birr against the Euro. This volatility behavior may affects the International Foreign Investment and trade balance of the country. Therefore, GJR-GARCH (2, 2) with student’s t-distribution is the best model both interms of the stylized facts and forecasting performance of the volatility of Ethiopian Birr/Euro exchange rate among others.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0151-6
      Issue No: Vol. 5, No. 4 (2018)
       
  • Fractal Dimension Calculation for Big Data Using Box Locality Index
    • Authors: Rong Liu; Robert Rallo; Yoram Cohen
      Pages: 549 - 563
      Abstract: The box-counting approach for fractal dimension calculation is scaled up for big data using a data structure named box locality index (BLI). The BLI is constructed as key-value pairs with the key indexing the location of a “box” (i.e., a grid cell on the multi-dimensional space) and the value counting the number of data points inside the box (i.e., “box occupancy”). Such a key-value pair structure of BLI significantly simplifies the traditionally used hierarchical structure and encodes only necessary information required by the box-counting approach for fractal dimension calculation. Moreover, as the box occupancies (i.e., the values) associated with the same index (i.e., the key) are aggregatable, the BLI grants the box-counting approach the needed scalability for fractal dimension calculation of big data using distributed computing techniques (e.g., MapReduce and Spark). Taking the advantage of the BLI, MapReduce and Spark methods for fractal dimension calculation of big data are developed, which conduct box-counting for each grid level as a cascade of MapReduce/Spark jobs in a bottom-up fashion. In an empirical validation, the MapReduce and Spark methods demonstrated good effectiveness and efficiency in fractal calculation of a big synthetic dataset. In summary, this work provides an efficient solution for estimating the intrinsic dimension of big data, which is essential for many machine learning methods and data analytics including feature selection and dimensionality reduction.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0152-5
      Issue No: Vol. 5, No. 4 (2018)
       
  • Transmuted Kumaraswamy Quasi Lindley Distribution with Applications
    • Authors: M. Elgarhy; I. Elbatal; Muhammad Ahsan ul Haq; Amal S. Hassan
      Pages: 565 - 581
      Abstract: The Lindley distribution is one of the widely used models for studying most of reliability modeling. Besides, several of researchers have motivated new classes of distributions based on modifications of the quasi Lindley distribution. In this article, a new version of generalized distributions named as the transmuted Kumaraswamy quasi Lindley (TKQL) is introduced. Various statistical properties of the TKQL distribution are provided. The rth moment of the TKQL distribution and its moment generating function are explored. Moreover, estimation of the model parameters is discussed via the method of maximum likelihood. Applications to real data are performed to clarify the flexibility of the TKQL distribution in comparison with some sub-models.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0153-4
      Issue No: Vol. 5, No. 4 (2018)
       
  • Exponentiated Power Lindley Logarithmic: Model, Properties and
           Applications
    • Authors: A. Shabani; M. Khaleghi Moghadam; A. Gholami; E. Moradi
      Pages: 583 - 613
      Abstract: A new class of lifetime distributions is proposed. Closed form expressions are provided for the density, cumulative distribution, survival and hazard rate functions. Maximum likelihood estimation is discussed and formulas for the elements of the observed information matrix are provided. Simulation studies are conducted. Finally, two real data applications are given showing the flexibility and potentiality of the new distribution
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0154-3
      Issue No: Vol. 5, No. 4 (2018)
       
  • Artificial Neural Network Classification of High Dimensional Data with
           Novel Optimization Approach of Dimension Reduction
    • Authors: Rabia Aziz; C. K. Verma; Namita Srivastava
      Pages: 615 - 635
      Abstract: Classification of high dimensional data is a very crucial task in bioinformatics. Cancer classification of the microarray is a typical application of machine learning due to the large numbers of genes. Feature (genes) selection and classification with computational intelligent techniques play an important role in diagnosis and prediction of disease in the microarray. Artificial neural networks (ANN) is an artificial intelligence technique for classifying, image processing and predicting the data. This paper evaluates the performance of ANN classifier using six different hybrid feature selection techniques, for gene selection of microarray data. These hybrid techniques use Independent component analysis (ICA), as an extraction technique, popular filter techniques and bio-inspired algorithm for optimization of the ICA feature vector. Five binary gene expression microarray datasets are used to compare the performance of these techniques and determine how these techniques improve the performance of ANN classifier. These techniques can be extremely useful in feature selection because they achieve the highest classification accuracy along with the lowest average number of selected genes. Furthermore, to check the significant difference between these different algorithms a statistical hypothesis test was employed with a certain level of confidence. The experimental result shows that a combination of ICA with genetic bee colony algorithm shows superior performance as it heuristically removes non-contributing features to improve the performance of classifiers.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0155-2
      Issue No: Vol. 5, No. 4 (2018)
       
  • On Optimal Progressive Censoring Schemes for Normal Distribution
    • Authors: U. H. Salemi; S. Rezaei; Y. Si; S. Nadarajah
      Pages: 637 - 658
      Abstract: Selection of optimal progressive censoring schemes for the normal distribution is discussed according to maximum likelihood estimation and best linear unbiased estimation. The selection is based on variances of the estimators of the two parameters of the normal distribution. The extreme left censoring scheme is shown to be an optimal progressive censoring scheme. The usual type-II right censoring case is shown to be the worst progressive censoring scheme for estimating the scale parameter. It can greatly increase the variance of estimators.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0156-1
      Issue No: Vol. 5, No. 4 (2018)
       
  • Joint Modeling of Longitudinal CD4 Count and Time-to-Death of HIV/TB
           Co-infected Patients: A Case of Jimma University Specialized Hospital
    • Authors: Aboma Temesgen; Abdisa Gurmesa; Yehenew Getchew
      Pages: 659 - 678
      Abstract: Tuberculosis (TB) and HIV have been closely linked since the emergence of AIDS; TB enhances HIV replication by accelerating the natural evolution of HIV infection which is the leading cause of sickness and death of peoples living with HIV/AIDS. To improve their life the co-infected patients are started to take antiretroviral treatment as patient started to take ART it is common to measure CD4 and other clinical outcomes which is correlated with survival time. However, the separate analysis of such data does not handle the association between the longitudinal measured out come and time-to-event where the joint modeling does to obtain valid and efficient survival time. Joint modeling of longitudinally measured CD4 and time-to death to understand their association. Furthermore, the study identifies factors affecting the mean change in square root CD4 measurement over time and risk factors for the survival time of HIV/TB co-infected patients. The study consists of 254 HIV/TB co-infected patients who were 18 years old or older and who were on antiretroviral treatment follow up from first February 2009 to fist July 2014 in Jimma University Specialized Hospital, West Ethiopia. First, data were analyzed using linear mixed model and survival models separately. After having appropriate separate models using Akaki information criteria, different joint models employed with different random effects longitudinal model and different shared parameters association structure of survival model and compared with deviance information criteria score. The linear mixed model showed functional status, weight, linear time and quadratic time effects have significant effect on the mean change of CD4 measurement over time. The Cox and Weibull survival model showed base line weight, baseline smoking, separated marital status group and base line functional status have significant effect on hazard function of the survival time whereas the joint model showed subject specific base line value; subject specific linear and quadratic slopes of CD4 measurement of were significantly associated with the survival time of co-infected patient at 5% significance levels. The longitudinally measured CD4 count measurement marker process is significantly associated with time to death and subject specific quadratic slope growth of CD4 measurement, base line clinical stage IV and smoking is the high risk factors that lower the survival time of HIV/TB co-infected patients. Since the longitudinally measured CD4 measurement is correlated with survival time joint modeling are used to handle the associations between these two processes to obtain valid and efficient survival time.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0157-0
      Issue No: Vol. 5, No. 4 (2018)
       
  • Statistical Inference and Optimum Life Testing Plans Under Type-II Hybrid
           Censoring Scheme
    • Authors: Tanmay Sen; Yogesh Mani Tripathi; Ritwik Bhattacharya
      Pages: 679 - 708
      Abstract: This article considers estimation of unknown parameters and prediction of future observations of a generalized exponential distribution based on Type-II hybrid censored data. Bayes point and HPD interval estimates of the unknown parameters are obtained under the assumption of independent gamma priors. Different classical and Bayesian point predictors and prediction intervals are obtained in two-sample situation against squared error loss function. The optimum censoring schemes are computed under various optimality criteria. Monte Carlo simulations are performed to compare different methods and two data sets are analyzed for illustrative purposes.
      PubDate: 2018-12-01
      DOI: 10.1007/s40745-018-0158-z
      Issue No: Vol. 5, No. 4 (2018)
       
  • On Some Further Properties and Application of Weibull- R Family of
           Distributions
    • Authors: Indranil Ghosh; Saralees Nadarajah
      Pages: 387 - 399
      Abstract: In this paper, we provide some new results for the Weibull-R family of distributions (Alzaghal et al. in Int J Stat Probab 5:139–149, 2016). We derive some new structural properties of the Weibull-R family of distributions. We provide various characterizations of the family via conditional moments, some functions of order statistics and via record values.
      PubDate: 2018-09-01
      DOI: 10.1007/s40745-018-0142-7
      Issue No: Vol. 5, No. 3 (2018)
       
  • A New Family of Generalized Distributions Based on Alpha Power
           Transformation with Application to Cancer Data
    • Authors: M. Nassar; A. Alzaatreh; O. Abo-Kasem; M. Mead; M. Mansoor
      Pages: 421 - 436
      Abstract: In this paper, we propose a new method for generating distributions based on the idea of alpha power transformation introduced by Mahdavi and Kundu (Commun Stat Theory Methods 46(13):6543–6557, 2017). The new method can be applied to any distribution by inverting its quantile function as a function of alpha power transformation. We apply the proposed method to the Weibull distribution to obtain a three-parameter alpha power within Weibull quantile function. The new distribution possesses a very flexible density and hazard rate function shapes which are very useful in cancer research. The hazard rate function can be increasing, decreasing, bathtub or upside down bathtub shapes. We derive some general properties of the proposed distribution including moments, moment generating function, quantile and Shannon entropy. The maximum likelihood estimation method is used to estimate the parameters. We illustrate the applicability of the proposed distribution to complete and censored cancer data sets.
      PubDate: 2018-09-01
      DOI: 10.1007/s40745-018-0144-5
      Issue No: Vol. 5, No. 3 (2018)
       
  • Region Based Instance Document (RID) Approach Using Compression Features
           for Authorship Attribution
    • Authors: N. V. Ganapathi Raju; Someswara Rao Chinta
      Pages: 437 - 451
      Abstract:
      Authors hip attribution is concerned with identifying authors of disputed or anonymous documents, which are potentially conspicuous in legal, criminal/civil cases, threatening letters and terroristic communications also in computer forensics. There are two basic approaches for authorship attribution one is instance based (treat each training text individually) and the other is profile based (treat each training text cumulatively). Both of these methods have their own advantages and disadvantages. The present paper proposes a new region based document model for authorship identification, to address the dimensionality problem of instance based approaches and scalability problem of profile based approaches. The proposed model concatenates a set of individual ‘n’ instance documents of the author as a single region based instance document (RID). On the RID compression based similarity distance method is used. The compression based methods requires no pre-processing and easy to apply. This paper uses Gzip compression algorithm with two compression based similarity measures NCD, CDM. The proposed compression model is character based and it can automatically capture easily non word features such as word stems, punctuations etc. The only disadvantage of compression models is complexity is high. The proposed RID approach addresses this issue by reducing the repeated words in the document. The present approach is experimented on English editorial columns. We achieved approximately 98% of accuracy in identifying the author.
      PubDate: 2018-09-01
      DOI: 10.1007/s40745-018-0145-4
      Issue No: Vol. 5, No. 3 (2018)
       
  • Development of Optimal ANN Model to Estimate the Thermal Performance of
           Roughened Solar Air Heater Using Two different Learning Algorithms
    • Authors: Harish Kumar Ghritlahre; Radha Krishna Prasad
      Pages: 453 - 467
      Abstract: In the present study, artificial neural network (ANN) model has been developed with two different training algorithms to predict the thermal efficiency of wire rib roughened solar air heater. Total 50 sets of data have been taken from experiments with three different types of absorber plate. The experimental data and calculated values of collector efficiency were used to develop ANN model. Scaled conjugate gradient (SCG) and Levenberg–Marquardt (LM) learning algorithms were used. It has been found that TRAINLM with 6 neurons and TRAINSCG with 7 neurons is optimal model on the basis of statistical error analysis. The performance of both the models have been compared with actual data and found that TRAINLM performs better than TRAINSCG. The value of coefficient of determination \((\hbox {R}^{2})\) for LM-6 is 0.99882 which gives the satisfactory performance. Learning algorithm with LM based proposed MLP ANN model seems more reliable for predicting performance of solar air heater.
      PubDate: 2018-09-01
      DOI: 10.1007/s40745-018-0146-3
      Issue No: Vol. 5, No. 3 (2018)
       
  • $$\ell _1$$ ℓ 1 -Norm Based Central Point Analysis for Asymmetric Radial
           Data
    • Authors: Qi An; Shu-Cherng Fang; Tiantian Nie; Shan Jiang
      Pages: 469 - 486
      Abstract: Multivariate asymmetric radial data clouds with irregularly positioned “spokes” and “clutters” are commonly seen in real life applications. In identifying the spoke directions of such data, a key initial step is to locate a central point from which each spoke extends and diverges. In this technical note, we propose a novel method that features a preselection procedure to screen out candidate points that have sufficiently many data points in the vicinity and identifies the central point by solving an \(\ell _1\) -norm constrained discrete optimization program. Extensive numerical experiments show that the proposed method is capable of providing central points with superior accuracy and robustness compared with other known methods and is computationally efficient for implementation.
      PubDate: 2018-09-01
      DOI: 10.1007/s40745-018-0147-2
      Issue No: Vol. 5, No. 3 (2018)
       
  • Enhancing Situation Awareness Using Semantic Web Technologies and Complex
           Event Processing
    • Authors: Havva Alizadeh Noughabi; Mohsen Kahani; Alireza Shakibamanesh
      Pages: 487 - 496
      Abstract: Data fusion techniques combine raw data of multiple sources and collect associated data to achieve more specific inferences than what could be attained with a single source. Situational awareness is one of the levels of the JDL, a matured information fusion model. The aim of situational awareness is to understand the developing relationships of interests between entities within a specific time and space. The present research shows how semantic web technologies, i.e. ontology and semantic reasoner, can be used to describe situations and increase awareness of the situation. As the situation awareness level receives data streams from numerous distributed sources, it is necessary to manage data streams by applying data stream processor engines such as Esper. In addition, in this research, complex event processing, a technique for achieving related situational in real-time, has been used, whose main aim is to generate actionable abstractions from event streams, automatically. The proposed approach combines Complex Event Processing and semantic web technologies to achieve better situational awareness. To show the functionality of the proposed approach in practice, some simple examples are discussed.
      PubDate: 2018-09-01
      DOI: 10.1007/s40745-018-0148-1
      Issue No: Vol. 5, No. 3 (2018)
       
  • Field Assignment, Field Choice and Preference Matching of Ethiopian High
           School Students
    • Authors: Derbachew Asfaw; Zeytu Gashaw
      Abstract: We examined the determinants of the admittance of students into their top wished-fields of study by university students using data from Ethiopian National Educational Assessment and Examination Agency. It is based on a 2016 cohort of 41,371 applicants in Social Science and 92,135 applicants in Natural Science, who were admitted to public universities in Ethiopia. We use a binary logistic regression model applied to four broadly defined fields in Social Science streaming and found that students’ place of residence, gender, EHEECE admission grade and age of the student have a significant positive impact on the decision process towards admitting students into their top wished-fields. Results also showed that there were significant positive interaction effects of EHEECE admission grade, gender and wished-fields on the decision process. We noticed a fair selection between girls and boys into the field of Law and Theatrical Fine Art and Music. For girls the odds of being admitted into the field of Other Social Science and Humanities were relatively better than the odds of being admitted into Business and Economics. We use a polytomous logit regression model applied to seven broadly defined fields in Natural Science streaming and found no selection bias in admitting applicants into the field of first and second ordered preferences among girls and boys, whilst there were a variation among the fields ranked thereafter.
      PubDate: 2018-10-03
      DOI: 10.1007/s40745-018-0182-z
       
  • A New Generalization of the Extended Exponential Distribution with an
           Application
    • Authors: Devendra Kumar; Manoj Kumar
      Abstract: We introduce a new lifetime distribution namely, transmuted extended exponential distribution which generalizes the extended exponential distribution proposed by Nadarajah and Haghighi (Statistics 45:543–558, 2011) with an additional parameter using the quadratic rank transmutation map which was studied by Shaw and Buckley (The alchemy of probability distributions: beyond Gram-Charlier expansions, and a skew-kurtotic-normal distribution from a rank transmutation map, 2009. arXiv:0901.0434) to provide greater flexibility in modeling data from a practical point of view. In this paper, our main focus is on estimation from frequentist point of view, yet, some statistical and reliability characteristics for the model are derived. We briefly describe different estimation procedures namely, the method of maximum likelihood estimation, maximum product of spacings estimation and least square estimation. Monte Carlo simulations are performed to compare the performance of the proposed methods of estimations for both small and large samples. Finally, the potentiality of the model is analyzed by means of one real data set.
      PubDate: 2018-09-22
      DOI: 10.1007/s40745-018-0181-0
       
  • A Primer on a Flexible Bivariate Time Series Model for Analyzing First and
           Second Half Football Goal Scores: The Case of the Big 3 London Rivals in
           the EPL
    • Authors: Yuvraj Sunecher; Naushad Mamode Khan; Vandna Jowaheer; Marcelo Bourguignon; Mohammad Arashi
      Abstract: The ranking of some English Premier League (EPL) clubs during football season is of keen interest to many stakeholders with special attention to the London rivals: Arsenal, Chelsea and Tottenham. In particular, the first (GF) and second half (GS) scores, besides being inter-related, is perceived as a convenient measure of the clubs potential. This paper studies the contributory effects of the possible factors that commonly influence the club scoring capacity in the halves along with forecasted measures diagnostics via a novel flexible bivariate time series model with COM-Poisson innovations using data from August 2014 to December 2017.
      PubDate: 2018-09-11
      DOI: 10.1007/s40745-018-0180-1
       
  • Treatment Effect Decomposition and Bootstrap Hypothesis Testing in
           Observational Studies
    • Authors: Hee Youn Kwon; Jason J. Sauppe; Sheldon H. Jacobson
      Abstract: Causal inference with observational data has drawn attention across various fields. These observational studies typically use matching methods which find matched pairs with similar covariate values. However, matching methods may not directly achieve covariate balance, a measure of matching effectiveness. As an alternative, the Balance Optimization Subset Selection (BOSS) framework, which seeks optimal covariate balance directly, has been proposed. This paper extends BOSS by estimating and decomposing a treatment effect as a combination of heterogeneous treatment effects from a partitioned set. Our method differs from the traditional propensity score subclassification method in that we find a subset in each subclass using BOSS instead of using the stratum determined by the propensity score. Then, by conducting a bootstrap hypothesis test on each component, we check the statistical significance of these treatment effects. These methods are applied to a dataset from the National Supported Work Demonstration (NSW) program which was conducted in the 1970s. By examining the statistical significance, we show that the program was not significantly effective to a specific subgroup composed of those who were already employed. This differs from the combined estimate—the NSW program was effective when considering all the individuals. Lastly, we provide results that are obtained when these steps are repeated with sub-samples.
      PubDate: 2018-09-08
      DOI: 10.1007/s40745-018-0179-7
       
 
 
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