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Parametric Statistical Theory

Parametric Statistical Theory is een boek van J. Pfanzagl;

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Statistical Paradigms

This volume consists of a collection of research articles on classical and emerging Statistical Paradigms parametric, non-parametric and;

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A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935

This book offers a detailed history of parametric statistical inference. Covering the period between James Bernoulli and R.A. Fisher, it;

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Introduction to Probability Theory and Statistical Inference

Discusses probability theory and to many methods used in problems of statistical inference. The Third Edition features material on;

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Empirical Process Techniques for Dependent Data

proved very useful for studying asymptotic properties of parametric as well as non-parametric statistical procedures. Recently, the need to model;

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Non-Standard Parametric Statistical Inference

This book discusses the fitting of parametric statistical models to data samples. Emphasis is placed on: (i) how to recognize situations;

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Mathematical Statistics

of statistical methodology. The author concentrates on inferential procedures within the framework of parametric models, but - acknowledging that;

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Inference and Prediction in Large Dimensions

/ or parameters belong to a large or infinite dimensional space. It develops the theory of statistical prediction, non-parametric estimation by;

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Statistical Models of Characteristics of Metal Vapor Lasers

In this book, various multivariate statistical techniques are applied in order to assess and predict the experiment. There are developed;

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BAYESIAN INFERENCE

. Topics covered include the central field of statistical inference as well as applications to areas of probability theory, information theory;

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Statistical Techniques in Geographical Analysis

of computational methods. Assuming no more than a good GCSE pass grade, the author covers the range of statistical techniques used by geographers, from;

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Mathematical Statistics

This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree;

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Advances In Statistical Modeling And Inference

data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and;

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Course in Mathematical Statistics and Large Sample Theory

mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered;

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Elements of Distribution Theory

in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are;

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Duration Analysis

Other than a common time-point related point of view on unemployment data, this book comprises different statistical methods to determine;

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Theory of Statistical Inference

Theory of Statistical Inference is designed as a reference on statistical inference for researchers and students at the graduate or;

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PDQ Statistics

PDQ Statistics is an overview of all major statistical methods, giving the reader a thorough understanding of statistics and how they are;

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Maximum Entropy and Bayesian Methods

include the common foundations for statistical inference, statistical physics and information theory. Specific sessions during the workshop;

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Fundamentals of Optical Parametric Processes and Oscillations

This monograph outlines the basic theory of optical parametric processes and presents discussions on materials and practical device;

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Event History Analysis: Statistical Theory and Application in the Social Sciences

models based upon concrete examples * presents the unabbreviated close relationship underlying statistical theory * details parameter;

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Predictive Inference

of approaches to prediction including those based on parametric, nonparametric, and nonstochastic statistical models, it is devoted mainly to predictive;

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Predictive Inference

of approaches to prediction including those based on parametric, nonparametric, and nonstochastic statistical models, it is devoted mainly to predictive;

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Constrained Statistical Inference

inference under inequality constraints and to apply the theory to problems in a variety of areas. Constrained Statistical Inference: Order;

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Nonparametric Tests for Complete Data

This book concerns testing hypotheses in non-parametric models. Classical non-parametric tests (goodness-of-fit, homogeneity, randomness;

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Nonparametric Tests for Censored Data

This book concerns testing hypotheses in non-parametric models. Generalizations of many non-parametric tests to the case of censored and;

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Core Statistics

parametric statistical models, including both theory and practical numerical computation. The book considers both frequentist maximum likelihood and;

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Einde inhoud

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