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Complex dynamic processes of life and sciences generate risks that have to be taken. The need for clear and distinctive definitions of different kinds...Savoir plus
From the reviews: "In this Lecture Note volume the author describes his differential-geometric approach to parametrical statistical problems summarizi...Savoir plus
Multivariate analysis has applications to many areas, including economics, psychology, and biometrics. The book develops the method of reduced rank re...Savoir plus
Monte Carlo methods are numerical methods based on random sampling and quasi-Monte Carlo methods are their deterministic versions. This volume contain...Savoir plus
This book provides a comprehensive treatment of the design of blocked and split-plot experiments. The optimal design approach advocated in the book wi...Savoir plus
This book is devoted to a number of stochastic models that display scale invariance. It primarily focuses on three issues: probabilistic properties, s...Savoir plus
Given a series of wind speeds and directions from the port of Fremantle the aim of this monograph is to detect general weather patterns and seasonal c...Savoir plus
The most widely used statistical method in seasonal adjustment is implemented in the X-11 Variant of the Census Method II Seasonal Adjustment Program....Savoir plus
With support from the University of Iowa and the Office of Naval Research. a small conference on order restricted inference was held at the University...Savoir plus
Scientists and engineers are increasingly making use of simulation methods to solve problems which are insoluble by analytical techniques. Monte Carlo...Savoir plus
This book offers a set of case studies exemplifying the broad range of statis- tical science used in environmental studies and application. The case s...Savoir plus
One of the charms of mathematics is the contrast between its generality and its applicability to concrete, even everyday, problems. Branching processe...Savoir plus
A stochastic process {X(t): 0 S t i}, i E S, are increasing (decreasing) with t on T. Stochastic monotonicity is a basic structural property for proce...Savoir plus
The theory of time series models has been well developed over the last thirt, y years. Both the frequenc.y domain and time domain approaches have been...Savoir plus
My interest in majorization was first spurred by Ingram aIkin's proclivity for finding Schur convex functions lurking in the problem section of every ...Savoir plus
Deconvolution problems occur in many ?elds of nonparametric statistics, for example, density estimation based on contaminated data, nonparametric - gr...Savoir plus
Robust statistics and the design of experiments are two of the fastest growing fields in contemporary statistics. Up to now, there has been very littl...Savoir plus
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the pow...Savoir plus
Recently new developments have taken place in the theory of nonpara- metric statistics for stochastic processes. Optimal asymptotic results have been ...Savoir plus
Smoothness Priors Analysis of Time Series addresses some of the problems of modeling stationary and nonstationary time series primarily from a Bayesia...Savoir plus
The theory and practice of decision making involves infinite or finite number of actions. The decision rules with a finite number of elements in the a...Savoir plus
Here, the authors explain the basic ideas so as to generate interest in modern problems of experimental design. The topics discussed include designs f...Savoir plus
This monograph is a collection of results recently obtained by the authors. Most of these have been published, while others are awaitlng publication. ...Savoir plus
The aso theory developed in Chapters 8 - 12 presumes that the tan- gent cones are linear spaces. In the present chapter we collect a few natural examp...Savoir plus