Simulation and Robust Statistics.pdf

Simulation and Robust Statistics PDF

Andreas Alfons

This book addresses the topics statistical simulation and robust estimation. It is accompanied by several software packages for the open source statistical computing environment R. Simulation studies are widely used by statisticians to gain insight into the quality of developed methods. In order to facilitate the implementation of simulation experiments, a general software framework for statistical simulation has been designed. However, simulation studies in survey statistics typically require population data, which are only in exceptions available to researchers. A method for generating close-to-reality population data for complex household surveys has thus been developed. Furthermore, confidentiality issues of such simulated population data are analyzed based on different worst case scenarios. The developed simulation methodology is used in two practical applications of robust statistics. First, semiparametric methods for robust estimation of indicators on poverty and social exclusion are evaluated. Second, a robust linear model selection procedure for applications in the social sciences has been developed and is applied in the context of quality of life research.

This volume features original contributions and invited review articles on mathematical statistics, statistical simulation and experimental design. The selected peer-reviewed contributions originate from the 8th International Workshop on Simulation held in Vienna in 2015. The book is intended for mathematical statisticians, Ph.D. students and

9783838127064 ISBN
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Simulation and Robust Statistics.pdf


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