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.

Statistical computing provides the link between statistical theory and applied statistics. The content of the book covers all aspects of this link, from the development and implementation of new statistical ideas to user experiences and software evaluation. The proceedings should appeal to anyone working in statistics and using computers, whether in universities, industrial companies, government agencies, research institutes or as software developers

In the last decades, the production of goods and the offer of services have become quite complex activities mostly because of the markets globalisation, of the continuous push to the innovation and of the constant requests from more and more demanding markets. The main objective of a company system has become the achievement of the quality for the business management cycle. This cycle goes from the design (Plan) to the production (Do), from the control (Check) to the man agement (Action), as well as to the marketing and distribution. Nowadays, the Total Quality of the company system is evaluated, according to the ISO 9000 regulations, in terms of its capacity to adjust the design and the pro duction to the needs expressed (explicitly or implictly) by the final users of a product/service. In this process, the use of statistical techniques is essential not only in the classical approach of Quality Control of a product but also, and most importantly, in the Quality Design oriented to the satisfaction of customers. Thus, Total Quality refers to the global capacity of a company to fit its system to the real needs of its customers by designing products which are able to match the customers' taste and by implementing a statistical control of both the product and the Customer Satisfaction. In such a process of design and evaluation, several statistical variables are involved and with a different nature (numerical, categorical, ordinal)."

Although no-one is, probably, too enthused about the idea, it is a fact that the development of most empirical sciences to a great extend depends of the development of data analysis methods and techniques, which, due to the necessity of applications of computers for that pur pose, actually means that it practically depends on the advancements and orientation of computational statistics. This volume contains complete texts of the lectures held during the Summer School on "Computational Aspects of Model Choice" orga nized jointly by Charles University, Prague, and International Associa tion for Statistical Computing (IASC) on July 1-14, 1991, in Prague. Main aims of the Summer School were to review and analyse some of the recent developments concerning computational aspects of the model choice as well as their theoretical background. The topics covers the problems of the change point detection, robust estimation and its computational aspects, classification using binary trees, stochastic ap proximation and optimization including the discussion about available software, computational aspects of graphical model selection and mul tiple hypotheses testing. The bridge between these different approaches is formed by the survey paper about statistical applications of artificial intelligence."

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.