Computational and Methodological Statistics and Biostatistics

1. Front Matter

   Pages i-xxiv

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2. Recent Developments in Theory and Applications of Statistical Distributions

   1. Front Matter

      Pages 1-1

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   2. Some Computational Aspects of Maximum Likelihood Estimation of the Skew-t Distribution

      • Adelchi Azzalini, Mahdi Salehi

      Pages 3-28

   3. Modelling Earthquakes: Characterizing Magnitudes and Inter-Arrival Times

      • Christophe Ley, Rosaria Simone

      Pages 29-50

   4. Multivariate Order Statistics Induced by Ordering Linear Combinations of Components of Multivariate Elliptical Random Vectors

      • Ahad Jamalizadeh, Roohollah Roozegar, Narayanaswamy Balakrishnan, Mehrdad Naderi

      Pages 51-71

   5. Variable Selection in Heteroscedastic Regression Models Under General Skew-t Distributional Models Using Information Complexity

      • Yeşim Güney, Olcay Arslan, Hamparsum Bozdogan

      Pages 73-98

   6. Weighted Condition Number Distributions Emanating from Complex Noncentral Wishart Type Matrices

      • Johannes T. Ferreira, Andriëtte Bekker

      Pages 99-119

   7. Weighted Type II Bivariate Pólya-Aeppli Distributions

      • Claire Geldenhuys, René Ehlers

      Pages 121-157

   8. Constructing Multivariate Distributions via the Dirichlet Generator

      • Mohammad Arashi, Andriëtte Bekker, Daniel de Waal, Seite Makgai

      Pages 159-186

   9. Evaluating Risk Measures Using the Normal Mean-Variance Birnbaum-Saunders Distribution

      • Mehrdad Naderi, Ahad Jamalizadeh, Wan-Lun Wang, Tsung-I Lin

      Pages 187-209

   10. On the Distribution of Linear Combinations of Chi-Square Random Variables

       • Carlos A. Coelho

       Pages 211-252

3. Recent Developments in Supervised and Unsupervised Modelling

   1. Front Matter

      Pages 253-253

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   2. Conjugate Bayesian Regression Models for Massive Geostatistical Data Sets

      • Sudipto Banerjee

      Pages 255-267

   3. Using Improved Robust Estimators to Semiparametric Model with High Dimensional Data

      • Mahdi Roozbeh, Nor Aishah Hamzah, Nur Anisah Mohamed

      Pages 269-290

   4. Optimal Allocation for Extreme Value Regression Under Time Censoring

      • Ping Shing Chan, Hon Yiu So, Hon Keung Tony Ng, Wei Gao

      Pages 291-307

   5. Spatial Interpolation of Extreme PM₁ Values Using Copulas

      • Alfred Stein, Fakhereh Alidoost, Vera van Zoest

      Pages 309-328

   6. A Scale Mixture Approach to t-Distributed Mixture Regression

      • Frans Kanfer, Sollie Millard

      Pages 329-347

   7. On Improving the Performance of Logistic Regression Analysis Via Extreme Ranking

      • Hani M. Samawi

      Pages 349-365

   8. Applications of Spatial Statistics in Poverty Alleviation in China

      • Yong Ge, Shan Hu, Mengxiao Liu

      Pages 367-392

4. Recent Developments in Biostatistics

   1. Front Matter

      Pages 393-393

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In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes.


Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia andindustry.


Computational and Methodological Statistics and Biostatistics is composed of three main themes:


•  Recent developments in theory and applications of statistical distributions;
•  Recent developments in supervised and unsupervised modelling;
•  Recent developments in biostatistics;


and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others. 

• Bayesian adaptive designs
• Bayesian statistics
• censoring
• circular distributions
• elliptical
• extreme values
• generalizability theory
• regression modeling
• mixture models
• optimization
• robust regression
• regression modelling
• spatio-temporal
• variable selection

• Department of Statistics, University of Pretoria, Pretoria, South Africa

  Andriëtte Bekker, (Din) Ding-Geng Chen, Johannes T. Ferreira

Dr. Andriëtte Bekker is a professor and the current head of the Department of Statistics at the Faculty of Natural and Agricultural Sciences, at the University of Pretoria. Her expertise lies in statistical distribution theory and comprises the study, development and expansion of distributions, and the addressing of parametric statistical inferential aspects, within the classical as well as the Bayesian framework. She is the academic research leader of the Statistical Theory and Applied Statistics focus area within the Department of Science and Technology/ National Research Foundation (DST-NRF) Centre of Excellence in Mathematical and Statistical Sciences, as well as  an elected member of the International Statistical Institute. Dr. Bekker has published more than 70 peer-reviewed papers in fundamental statistical research.

Dr. Ding-Geng Chen is a fellow of American Statistical Association and currently the Wallace Kuralt distinguished professor at the University of North Carolina at Chapel Hill as well as the South Africa DST-NRF-SAMRC, SARChI in Biostatistics (Tier 1). He was a professor in biostatistics at the University of Rochester and the Karl E. Peace endowed eminent scholar chair in biostatistics at Georgia Southern University. He is also a senior statistics consultant for biopharmaceuticals and government agencies with extensive expertise in Monte-Carlo simulations, clinical trial biostatistics and public health statistics. Dr. Chen has more than 150 referred professional publications and co-authored and co-edited twenty-three books on clinical trial methodology, meta-analysis and public health applications. He has been invited nationally and internationally to give speeches on his research.

Dr. Johan Ferreira is currently a senior lecturer in the Department of Statistics at the University of Pretoria, South Africa, and is Junior Focus Area Coordinator for the Statistical Theory and Applied Statistics focus area ofthe Centre of Excellence in Mathematical and Statistical Science based at the University of the Witwatersrand in Johannesburg. He regularly publishes in accredited peer-reviewed journals and reviews manuscripts for international journals. He is an ASLP 4.1/4.2 fellow of Future Africa and has been identified as one of the Top 200 South Africans under the age of 35 by the Mail & Guardian newspaper in the Education category in 2016.

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