Jaromír Antoch – författare

This volume collects authoritative contributions on analytical methods and mathematical statistics. The methods presented include resampling techniques; the minimization of divergence; estimation theory and regression, eventually under shape or other constraints or long memory; and iterative approximations when the optimal solution is difficult to achieve. It also investigates probability distributions with respect to their stability, heavy-tailness, Fisher information and other aspects, both asymptotically and non-asymptotically. The book not only presents the latest mathematical and statistical methods and their extensions, but also offers solutions to real-world problems including option pricing. The selected, peer-reviewed contributions were originally presented at the workshop on Analytical Methods in Statistics, AMISTAT 2015, held in Prague, Czech Republic, November 10-13, 2015.

This volume collects authoritative contributions on analytical methods and mathematical statistics. The selected, peer-reviewed contributions were originally presented at the workshop on Analytical Methods in Statistics, AMISTAT 2015, held in Prague, Czech Republic, November 10-13, 2015.

This volume contains complete texts of the lectures held during a Summer School on Computational Aspects of Model Choice, organized jointly by the International Association for Statistical Computing and Charles University, Prague. The main aims of the school were to review and analyze some of the recent developments concerning computational aspects of the model choice as well as their theoretical background. The topics cover problems of change point detection, robust estimating and its computational aspects, classification using binary trees, stochastic approximation and optimization, including a discussion about available software, computational aspects of graphical model selection and multiple hypotheses testing.

The major focus of the book is on using the methods suitable for an on-line and off-line process control both in the univariate and multivariate case. The authors not only concentrate on the standard situation when the errors accompanying the observed process are normally distributed, but also describe in detail the more general situations that call for the use of the robust and non-parametric approaches. Within these approaches, the use of recent methods of the multivariate analysis in the total quality control is enhanced with particular reference to the customer satisfaction area, the monitoring of interval data and the comparison of patterns generated from multioccasion observations. The authors cover both practical computational aspects of the problem and the necessary mathematical background, taking into account requirements of total quality control.