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Testing For Normality

Describes the selection, design, theory, and application of tests for normality. Covers robust estimation, test power, and univariate and;

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Testing For Normality

Describes the selection, design, theory, and application of tests for normality. Covers robust estimation, test power, and univariate and;

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Introduction to Robust Estimation and Hypothesis Testing

in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications;

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A Concise Guide to Statistics

examples are provided. T-tests are used throughout, followed important other tests and robust/nonparametric alternatives. Multiple testing;

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Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful 'how-to' on the application of robust methods utilizing;

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Beyond Significance Testing

Traditional education in statistics that emphasises significance testing leaves researchers and students ill prepared to understand what;

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Robust Estimation And Testing

Offering an introduction to the theory and methods of robust statistics at an intermediate level, this work aims to illustrate the need for;

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Power System State Estimation

, and guidelines to clearly examine new aspects of state estimation, the testing of network observability, and methods to assure computational;

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Statistical Inference

testing and interval estimation are all covered thoroughly, with recent developments outlined. Separate chapters are devoted to Bayesian inference;

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Optimal and Robust Estimation

today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second;

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An Introduction to Nonparametric Statistics

techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention is paid to the intellectual;

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Methodology in Robust and Nonparametric Statistics

estimation with special emphasis on affine-equivariant procedures, followed by hypotheses testing and confidence sets Keeps mathematical;

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Methodology in Robust and Nonparametric Statistics

statistical procedures. Thoroughly up-to-date, this book Presents multivariate robust and nonparametric estimation with special emphasis on affine;

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Elements of Adaptive Testing

of the test taker's ability estimate. This book covers such key features of adaptive testing as item selection and ability estimation, adaptive;

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Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon,is a 'how-to' on the application of robust methods using available;

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High-Resolution and Robust Signal Processing

of parametric high-resolution estimation and detection techniques; robust array processing solutions for adaptive beam forming and high-resolution;

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Unit Roots, Cointegration, and Structural Change

unit root testing, estimation of cointegration systems, cointegration tests, and econometric estimation with integrated regressors. The authors;

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Robustness Theory and Application

A preeminent expert in the field explores new and exciting methodologies in the ever-growing field of robust statistics Used to develop;

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Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems

, advanced robust observer structures are presented. Parameter estimation based techniques are discussed as well. A particular attention is drawn to;

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Robust Methods in Biostatistics

methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general;

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Stable Adaptive Control And Estimation For Nonlinear Systems

* Includes a solution manual for problems.* Provides MATLAB code for examples and solutions.* Deals with robust systems in both theory and;

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Accurate and Robust Spectral Testing with Relaxed Instrumentation Requirements

This book introduces a family of new methods for accurate and robust spectral testing and fills an information gap, as the requirements;

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Algorithms for Regression and Classification

regression, new exact algorithms, results for robust online scale estimation, and an evolutionary computation algorithm for different estimators;

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Advances on Methodological and Applied Aspects of Probability and Statistics

researchers on the topic, present several different subspecialties, including applied probability, models and applications, estimation and testing;

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Advances on Methodological and Applied Aspects of Probability and Statistics

researchers on the topic, present several different subspecialties, including applied probability, models and applications, estimation and testing;

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Simulation and Robust Statistics

This book addresses the topics statistical simulation and robust estimation. It is accompanied by several software packages for the open;

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Robust Kalman Filtering for Signals and Systems With Large Uncertainties

cover the theory of robust state estimation for the case in which the process model contains significant uncertainties and non-linearities.;

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