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Computational and Methodological Statistics and Biostatistics

Contemporary Essays in Advancement

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

ca. 96,29
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Naturwissenschaften, Medizin, Informatik, Technik / Allgemeines


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 and industry.

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. 

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