Applied Statistical Methods
ISGES 2020, Pune, India, January 2-4
(Sprache: Englisch)
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...
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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.
Inhaltsverzeichnis zu „Applied Statistical Methods “
X. Chen and B. Nandram, Bayesian Order-Restricted Inference of Multinomial Counts from Small Areas.- L. Chen and B. Nandram, A Hierarchical Bayesian Beta-Binomial Model for Sub-Areas.- P. Anjoy and H. Chandra, Hierarchical Bayes Prediction of Survey-Weighted Small Area Proportions.- E. Zamanzade1 and M. Mahdizadeh, Efficiency of Ranked Set Sampling Design in Goodness of Fit Tests for Cauchy Distribution.- M. R. Bhosale1, R. Latpate and S. Gitte, Fuzzy Supply Chain Newsboy Problem Under Lognormal Distributed Demand for Bakery Products.- S. Kurade, R. Latpate and D. Hanagal, Probabilistic Supply Chain Models with Partial Backlogging for Deteriorating Items.- P. Ranjan and M. Harshvardhan, The Evolution of Dynamic Gaussian Process Model with Applications to Malaria Vaccine Coverage Prediction.- K. Uniyal1, G. Chandra, R. U. Khan and Y. P. Singh, Grey Relational Analysis for the Selection of Potential Isolates of Alternaria Alternata of Poplar.- Nidhi D. Raykundaliya and DharmeshP. Raykundaliya.- Decision making for Multi-items Inventory Models.- A. Pandey, David D. Hanagal, S. Tyagi and P. Gupta, Modeling Australian Twin Data using Generalized Lindley Shared Frailty Models, K. Jain and H. S. Kapoor, Ultimate Ruin Probability for Benktander Gibrat Risk Model, K. K. Mahajan, S. Arora and A. Gaur, Test of Homogeneity of Scale Parameters Based on Function of Sample Quasi Ranges.- T. Dai and Sanjay Shete, A Bayesian Response-Adaptive, Covariate-Balanced and Q-learning-Decision-consistent Randomization Method for SMART Designs.- J. Sedransk, An introduction to Bayesian Inference for Finite Population Characteristics.- S. C. Malik, Reliability Measures of Repairable Systems with Arrival Time of Server.- P. V. Pandit and S. Joshi, Stress-Strength Reliability estimation for Multi-component system Based on Upper Record Values under New Weibull-Pareto Distribution.- V. S. Vaidyanathan and H. Bakouch, Record Values and Associated Inference on Muth Distribution.- Shalabh,
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Statistical Linear Calibration in Data with Measurement Errors.
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Autoren-Porträt
DAVID D. HANAGAL is Honorary Professor at Symbiosis Statistical Institute, Symbiosis International University, Pune, India. Earlier, he was Professor at the Department of Statistics, Savitribai Phule Pune University, Maharashtra, India. He also has worked as a visiting professor at several universities in the USA, Germany, and Mexico. His research interests include statistical inference, selection problems, reliability, survival analysis, frailty models, Bayesian inference, stress-strength models, Monte-Carlo methods, MCMC algorithms, bootstrapping, censoring schemes, distribution theory, multivariate models, characterizations, repair and replacement models, software reliability, quality loss index, and nonparametric inference.... mehr
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.
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.
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Bibliographische Angaben
- 2022, 1st ed. 2022, XVIII, 307 Seiten, 28 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Gebunden, Englisch
- Herausgegeben: David D. Hanagal, Raosaheb V. Latpate, Girish Chandra
- Verlag: Springer, Berlin
- ISBN-10: 9811679312
- ISBN-13: 9789811679315
Sprache:
Englisch
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