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Advances in Statistics - Theory and Applications


Advances in Statistics - Theory and Applications

Honoring the Contributions of Barry C. Arnold in Statistical Science
Emerging Topics in Statistics and Biostatistics

von: Indranil Ghosh, N. Balakrishnan, Hon Keung Tony Ng

128,39 €

Verlag: Springer
Format: PDF
Veröffentl.: 01.04.2021
ISBN/EAN: 9783030629007
Sprache: englisch

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Beschreibungen

This edited collection brings together internationally recognized experts in a range of areas of statistical science to honor the contributions of the distinguished statistician, Barry C. Arnold. A pioneering scholar and professor of statistics at the University of California, Riverside, Dr. Arnold has made exceptional advancements in different areas of probability, statistics, and biostatistics, especially in the areas of distribution theory, order statistics, and statistical inference. As a tribute to his work, this book presents novel developments in the field, as well as practical applications and potential future directions in research and industry. It will be of interest to graduate students and researchers in probability, statistics, and biostatistics, as well as practitioners and technicians in the social sciences, economics, engineering, and medical sciences.<br>
1. Wrapped gamma distribution for modeling and inference with asymmetric circular data - Ashis SenGupta, Carlos A. Coelho, Choung Min Ng.- 2. Goodness of fit tests for Cauchy distributions using data transformations - Jose A. Villasenor.- 3. A note on the product of independent beta random variables - Filipe J. Marques, Indranil Ghosh, Johan Ferreira, Andriette Bekker.- 4. Properties of system lifetime distributions in the classic model of independent exponential component lifetimes - Tomasz Rychlik.- 5. On the exact statistical distribution of econometric estimators and test statistics - Yong Bao, Xiaotian Liu, Aman Ullah.- 6. On conditional tail inferences from multivariate distributions - Harry Joe.- 7. A bivariate distribution with generalized exponential conditionals: Theory and applications - Miroslav Ristic, Bozidar V. Popovic, Indranil Ghosh.- 8. Assessment of distributional goodness-of-fit for modeling the superposition of renewal process data - Wei Zhang, William Q. Meeker.- 9. Skew-Elliptical Thomas point processes - Ngoc Anh Dao, Marc G. Genton.- 10. Bayesian model assessment and selection using Bregman divergence - Gyuhyeong Goh, Dipak K. Dey.- 11. On hidden truncation in non-normal models - Indranil Ghosh, Hon Keung Tony Ng.
<div><div><b>Indranil Ghosh</b>&nbsp;is an Associate Professor of Statistics in the Department of Mathematics and Statistics at the University of North Carolina Wilmington, USA. Currently, he is serving as a guest editor for a special issue of the journal <i>Computational and Mathematical Methods</i> (John Wiley & Sons) and on the editorial board of the <i>Journal of Business Analytics</i> (Taylor & Francis), and is an associate editor for the <i>Journal of the Iranian Statistical Society</i>. He is the Chair-Elect 2021 of the Section on Risk Analysis of the American Statistical Association, and an elected member of the International Statistical Institute.</div><div><b><br></b></div><div><b>Narayanaswamy Balakrishnan</b>, Distinguished University Professor, is in the Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada. Professor Balakrishnan is an internationally recognized expert on many areas of statistics, including statistical distribution theory and ordered data analysis. He is currently the Editor-in-Chief of <i>Communications in Statistics</i>&nbsp;(Taylor & Francis), and was previously the Editor-in-Chief for the revised version of <i>Encyclopedia of Statistical Sciences</i>&nbsp;(John Wiley & Sons). He is a Fellow of the American Statistical Association and a Fellow of the Institute of Mathematical Statistics, and in 2016 he received an Honorary Doctorate from The National and Kapodistrian University of Athens, Greece.</div><div><b><br></b></div><b>Hon Keung Tony Ng</b> is a Professor of Statistical Science with the Southern Methodist University, Dallas, TX, USA. He is an associate editor of <i>Communications in Statistics</i>, <i>Computational Statistics</i>, <i>IEEE Transactions on Reliability</i>, <i>Journal of Statistical Computation and Simulation</i>, <i>Naval Research Logistics</i>, <i>Sequential Analysis</i> and <i>Statistics & Probability Letters</i>. His research interests include reliability, censoring methodology, ordered data analysis, nonparametric methods, and statistical inference. He is the co-editor of <i>Ordered Data Analysis, Modeling and Health Research Methods</i>, <i>Statistical Modeling for Degradation Data</i>, and <i>Statistical Quality Technologies:</i>&nbsp;<i>Theory and Practice</i> (all published by Springer). He is a Fellow of the American Statistical Association, an elected senior member of IEEE and an elected member of the International Statistical Institute.</div><div><br></div>
This edited collection brings together internationally recognized experts in a range of areas of statistical science to honor the contributions of the distinguished statistician, Barry C. Arnold. A pioneering scholar and professor of statistics at the University of California, Riverside, Dr. Arnold has made exceptional advancements in different areas of probability, statistics, and biostatistics, especially in the areas of distribution theory, order statistics, and statistical inference. As a tribute to his work, this book presents novel developments in the field, as well as practical applications and potential future directions in research and industry. It will be of interest to graduate students and researchers in probability, statistics, and biostatistics, as well as practitioners and technicians in the social sciences, economics, engineering, and medical sciences.
<p>Features research topics inspired by the substantial contributions of Professor Barry C. Arnold to probability and statistics, in areas such as distribution theory, order statistics, stochastic processes, statistical modeling, characterizations, inequality measurement, multivariate distributions, and statistical inference</p><p>Provides the timely updates and recent developments on some essential and emerging areas of probability, statistics, and biostatistics</p><p>Presents some novel statistical methodologies and theories and the related important future research directions as well as potential practical applications in social sciences, economics, engineering, and medical sciences</p>

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