Publisher: Science and Education Publishing   (Total: 75 journals)   [Sort by number of followers]

Showing 1 - 75 of 75 Journals sorted alphabetically
American J. of Applied Mathematics and Statistics     Open Access   (Followers: 10)
American J. of Applied Psychology     Open Access   (Followers: 50)
American J. of Biomedical Research     Open Access   (Followers: 2)
American J. of Cancer Prevention     Open Access   (Followers: 7)
American J. of Civil Engineering and Architecture     Open Access   (Followers: 40)
American J. of Clinical Medicine Research     Open Access   (Followers: 5)
American J. of Educational Research     Open Access   (Followers: 62)
American J. of Electrical and Electronic Engineering     Open Access   (Followers: 26)
American J. of Energy Research     Open Access   (Followers: 7)
American J. of Environmental Protection     Open Access   (Followers: 4)
American J. of Epidemiology and Infectious Disease     Open Access   (Followers: 14)
American J. of Food and Nutrition     Open Access   (Followers: 46)
American J. of Food Science and Technology     Open Access   (Followers: 3)
American J. of Infectious Diseases and Microbiology     Open Access   (Followers: 23)
American J. of Information Systems     Open Access   (Followers: 4)
American J. of Materials Engineering and Technology     Open Access   (Followers: 3)
American J. of Materials Science and Engineering     Open Access   (Followers: 7)
American J. of Mathematical Analysis     Open Access   (Followers: 1)
American J. of Mechanical Engineering     Open Access   (Followers: 64)
American J. of Medical and Biological Research     Open Access   (Followers: 3)
American J. of Medical Case Reports     Open Access   (Followers: 1)
American J. of Medical Sciences and Medicine     Open Access   (Followers: 2)
American J. of Medicine Studies     Open Access   (Followers: 3)
American J. of Microbiological Research     Open Access   (Followers: 4)
American J. of Modeling and Optimization     Open Access   (Followers: 2)
American J. of Nanomaterials     Open Access   (Followers: 6)
American J. of Numerical Analysis     Open Access   (Followers: 1)
American J. of Nursing Research     Open Access   (Followers: 5)
American J. of Pharmacological Sciences     Open Access   (Followers: 1)
American J. of Public Health Research     Open Access   (Followers: 30)
American J. of Rural Development     Open Access   (Followers: 5)
American J. of Sensor Technology     Open Access   (Followers: 2)
American J. of Sports Science and Medicine     Open Access   (Followers: 39)
American J. of Water Resources     Open Access   (Followers: 10)
American J. of Zoological Research     Open Access   (Followers: 4)
Applied Ecology and Environmental Sciences     Open Access   (Followers: 29)
Applied Mathematics and Physics     Open Access   (Followers: 3)
Automatic Control and Information Sciences     Open Access   (Followers: 4)
Biomedical Science and Engineering     Open Access   (Followers: 5)
Chemical Engineering and Science     Open Access   (Followers: 58)
Intl. J. of Celiac Disease     Open Access  
Intl. J. of Dental Sciences and Research     Open Access   (Followers: 1)
Intl. J. of Econometrics and Financial Management     Open Access   (Followers: 4)
Intl. J. of Physics     Open Access   (Followers: 10)
Intl. Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
J. of Automation and Control     Open Access   (Followers: 10)
J. of Biomedical Engineering and Technology     Open Access  
J. of Business and Management Sciences     Open Access  
J. of Cancer Research and Treatment     Open Access   (Followers: 3)
J. of Computer Networks     Open Access   (Followers: 6)
J. of Computer Sciences and Applications     Open Access  
J. of Environment Pollution and Human Health     Open Access   (Followers: 3)
J. of Finance and Accounting     Open Access   (Followers: 8)
J. of Finance and Economics     Open Access   (Followers: 13)
J. of Food and Nutrition Research     Open Access   (Followers: 9)
J. of Food Security     Open Access   (Followers: 2)
J. of Geosciences and Geomatics     Open Access   (Followers: 1)
J. of Materials Physics and Chemistry     Open Access   (Followers: 7)
J. of Mathematical Sciences and Applications     Open Access   (Followers: 2)
J. of Optoelectronics Engineering     Open Access   (Followers: 5)
J. of Physical Activity Research     Open Access   (Followers: 3)
J. of Polymer and Biopolymer Physics Chemistry     Open Access   (Followers: 7)
Materials Science and Metallurgy Engineering     Open Access   (Followers: 8)
Nanoscience and Nanotechnology Research     Open Access   (Followers: 21)
Physics and Materials Chemistry     Open Access   (Followers: 1)
Research in Plant Sciences     Open Access  
Research in Psychology and Behavioral Sciences     Open Access   (Followers: 2)
Sustainable Energy     Open Access   (Followers: 2)
Turkish J. of Analysis and Number Theory     Open Access  
Wireless and Mobile Technologies     Open Access   (Followers: 4)
World J. of Agricultural Research     Open Access  
World J. of Analytical Chemistry     Open Access   (Followers: 3)
World J. of Chemical Education     Open Access   (Followers: 2)
World J. of Environmental Engineering     Open Access   (Followers: 1)
World J. of Organic Chemistry     Open Access   (Followers: 5)
Similar Journals
Journal Cover
American Journal of Applied Mathematics and Statistics
Number of Followers: 10  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2328-7306 - ISSN (Online) 2328-7292
Published by Science and Education Publishing Homepage  [75 journals]
  • Concept of Sub-Independence and Characterizations of 2SQLindley and
           2DQLindley Distributions

    • Authors: G.G. Hamedani
      Pages: 39 - 43
      Abstract: Amer et al. [1] considered the distributions of the sum and the difference of two independent and identically distributed random variables with the common Quasi Lindley distribution. They derived, very nicely, the above mentioned distributions and provided certain important mathematical and statistical properties as well as simulations and applications of the new distributions. Wang and Ma [2] considered the sum of the gamma random variables under the assumption of independence of the summands and presented very interesting results. In this short note, we like to show that the assumption of "independence" can be replaced with a much weaker assumption of "sub-independence" in both papers. Then we present certain characterizations of the distributions derived by Amer et al. [1], called 2SQLindley and 2DQLindley distributions.
      PubDate: 2022-04-27
      DOI: 10.12691/ajams-10-2-1
      Issue No: Vol. 10, No. 2 (2022)
       
  • Features Selection in Statistical Classification of High Dimensional Image
           Derived Maize (Zea Mays L.) Phenomic Data

    • Authors: Peter Gachoki; Moses Muraya, Gladys Njoroge
      Pages: 44 - 51
      Abstract: Phenotyping has advanced with the application of high throughput phenotyping techniques such automated imaging. This has led to derivation of large quantities of high dimensional phenotypic data that could not have been achieved using manual phenotyping in a single run. Hence, the need for parallel development of statistical techniques that can appropriately handle such large and/or high dimensional data set. Moreover, there is need to come up with a statistical criteria for selecting the best image derived phenotypic features that can be used as best predictors in modelling plant growth. Information on such criteria is limited. The objective of this study is to apply feature importance, feature selection with Shapley values and LASSO regression techniques to find the subset of features with the highest predictive power for subsequent use in modelling maize plant growth using high-dimensional image derived phenotypic data. The study compared the statistical power of these features extraction methods by fitting an XGBoost model using the best features from each selection method. The image derived phenomic data was obtained from Leibniz Institute of Plant Genetics and Crop Plant Research, -Gatersleben, Germany. Data analysis was performed using R-statistical software. The data was subjected to data imputation using k Nearest Neighbours technique. Features extraction was performed using feature importance, Shapley values and LASSO regression. The Shapley values extracted 25 phenotypic features, feature importance extracted 31 features and LASSO regression extracted 12 features. Of the three techniques, the feature importance criterion emerged the best feature selection technique, followed by Shapley values and LASSO regression, respectively. The study demonstrated the potential of using feature importance as a selection technique in reduction of input variables in of high dimensional growth data set.
      PubDate: 2022-06-06
      DOI: 10.12691/ajams-10-2-2
      Issue No: Vol. 10, No. 2 (2022)
       
 
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