Applied Statistical Methods
Description
This book collects select contributions presented at the International Conference on Importance of Statistics in Global Emerging (ISGES 2020) held at the Department of Mathematics and Statistics, University of Pune, Maharashtra, India, from 2-4 January 2020. It discusses recent developments in several areas of statistics with applications of a wide range of key topics, including small area estimation techniques, Bayesian models for small areas, ranked set sampling, fuzzy supply chain, probabilistic supply chain models, dynamic Gaussian process models, grey relational analysis and multi-item inventory models, and more. The possible use of other models, including generalized Lindley shared frailty models, Benktander Gibrat risk model, decision-consistent randomization method for SMART designs and different reliability models are also discussed. This book includes detailed worked examples and case studies that illustrate the applications of recently developed statistical methods, making it a valuable resource for applied statisticians, students, research project leaders and practitioners from various marginal disciplines and interdisciplinary research.
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With more than 40 years of teaching experience and more than 35 years of research experience, he is an expert on writing programs by using SAS, R, MATLAB, MINITAB, SPSS, and SPLUS statistical packages. He has supervised nine PhD students in different areas of statistics namely, reliability, survival analysis, frailty models, repair and replacement models, software reliability, and quality loss index. An elected fellow of the Royal Statistical Society, UK, he is an editor and on the editorial board of several respected international journals. He has authored four books, three book-chapters and published more than 130 research publications in leading journals. He has delivered more than 100 invited talks in many national and international platforms of repute worldwide.
RAOSAHEB V. LATPATE is Assistant Professor at the Department of Statistics and Center for Advanced Studies, Savitribai Phule Pune University, Maharashtra, India. After his graduation from the Department of Statistics, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India, in 2005, he earned his PhD degree from the same university. His research interests include genetic algorithm, fuzzy set theory, supply chain management, logistics and transportation problem, simulation and modelling, and sample survey. He has organized three international conferences and three national conference, workshop, and faculty development programme on statistical methods and applications. He is member of several professional societies and institutions, including the International Statistical Institute, International Indian Statistical Association, the Society for Statistics and Computer Applications, and the Indian Society for Probability and Statistics.
GIRISH CHANDRA is Scientist in the Division of Forestry Statistics, Indian Council of Forestry Research and Education (ICFRE), Dehradun, an autonomous body under the Ministry of Environment, Forest and Climate Change, Government of India, in Uttrakhand. Before joining ICFRE in 2013, he worked at the Tropical Forest Research Institute, Jabalpur, and at Central Agricultural University, Sikkim, India, for more than seven years. He is a recipient of the Cochran-Hansen Prize 2017 of the International Association of Survey Statisticians, the Netherlands. He also is honored with ICFRE Outstanding Research Award 2018 besides the Young Scientist Award in Mathematical Sciences from the Government of Uttarakhand, India. He has published over 45 research papers in various respected journals and have three books to his credit. He has organised two national conferences on forestry and environmental statistics. He is member of various scientific institutions, including the International Statistical Institute, International Indian Statistical Association, Computational and Methodological Statistics, Indian Society of Probability and Statistics.
