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Aims to provide in-depth descriptions of the latest developments in multiple comparison methods and selection procedures, while emphasizing biometry. This text is published in honour of the 70th birthday of Charles W. Dunnett - a pioneer in statistical methodology.
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Beginning with the historical background of probability theory, this text examines various important aspects of mathematical probability - including random... Læs mere
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The ingratiating title notwithstanding, this is in no standard sense a text but a monograph, based largely upon the authors' research over a period of years, and intended... Læs mere
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This book presents a study of order statistics from standard Inverse Gaussian distributions and their... Læs mere
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This book explains how the computer programs work and why and when they can be applied to problems in toxicology. It discusses the statistical models used and their... Læs mere
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This book demonstrates how numbers open up new ways of thinking about problems and addresses current issues for which statistics has practical applications. The articles... Læs mere
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Designed to make theory work for students, this clearly written, easy-to-understand work serves as the ideal texts for courses Regression,... Læs mere
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This book provides a comprehensive study of the bivariate discrete distributions and details the computer simulation techniques for the distributions. It develops... Læs mere
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This text presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view.... Læs mere
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Encourages development of application and decision making skills for use in managing raw data and real-world projects. This book includes such topics as scattergrams and time series graphs, simple and multiple regressions, time series analysis, and random sampling.
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Bemærk: Kan ikke leveres før jul.
This book investigates some simple stochastic models and shows how there is an interplay between the models and the science underlying the problem. It combines stochastic modeling and statistical inference in point processes, Markov random fields, and hidden Markov models.