Ajit Kumar Majumder (11 results)

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rahman Md. MahabuburRight now, Dr. Md. Mahabubur Rahman is working as an Associate Professor in the Department of Statistics at Islamic University, Bangladesh. He received a Ph.D. degree in Statistics from KAU, KSA. He has published .…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hossain Md. MoyazzemCurrently, Md. Moyazzem Hossain working as an Assistant Professor in the department of Statistics at Jahangirnagar University, Bangladesh. He has published more than 45 research articles in national and internatio.…

Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rois RumanaRumana Rois is an Assistant Professor in the Department of Statistics at Jahangirnagar University, where she has taught since 2006. Rois received her B.Sc. and M.Sc. degree in Statistics. She has published over 12 articles.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rahman Md. SiddikurMd. Siddikur Rahman is working in the Department of Applied Statistics at East West University since January 2013. He received his M.S. and B.Sc degree in Statistics from Jahangirnagar University, Bangladesh.His R.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This text considers different parametric and nonparametric classification techniques to classify objects, and make a comparative study among these techniques. In most of the situations, classification techniques give few misclassifications under large samples as well as under the normal populations. If the data set comes from the non-normal populations, then we apply Box-Cox transformation to transform this data set into near normal. Hence, we investigate the effect of Box-Cox transformation and see that Box-Cox transformed data generates better discrimination and classification techniques. Also if the sample size is small, then we use the Bootstrap approach for classifying objects, and investigate that the Bootstrap classification technique used in this analysis performs better than the usual techniques of small samples. There is no unique classification technique that is suitable for all the situations, also examines that nonparametric classification techniques perform better than the parametric classification techniques, whereas the Neural Network classification technique gives optimum solutions among the nonparametric classification techniques.…