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Nonparametric Statistics And Mixture Models

in research in nonparametric statistics, rank statistics, robustness, and mixture models during a career that spanned nearly 40 years. It is a broad;

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All of Nonparametric Statistics

method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and;

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Nonparametric Models for Longitudinal Data

Discusses nonparametric shared-parameter and mixed-effects models Presents nonparametric models for conditional distributions and;

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Nonparametric Econometrics

This book systematically and thoroughly covers the vast literature on the nonparametric and semiparametric statistics and econometrics that;

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Nonparametric Econometrics

This book systematically and thoroughly covers the vast literature on the nonparametric and semiparametric statistics and econometrics that;

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Nonparametric Models for Longitudinal Data

. Features: * Provides an overview of parametric and semiparametric methods * Shows smoothing methods for unstructured nonparametric models;

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Cambridge Series in Statistical and Probabilistic Mathematics

The theory of empirical processes provides valuable tools for the development of asymptotic theory in (nonparametric) statistical models;

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Mathematical Statistics

nonparametric techniques. It covers topics in parametric and nonparametric large-sample estimation theory. The exposition is based on a collection;

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Nonparametric Smoothing and Lack-of-Fit Tests

problems. As such, the book is of interest to practitioners of statistics and researchers investigating either lack-of-fit tests or nonparametric;

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Methodology in Robust and Nonparametric Statistics

Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from;

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Methodology in Robust and Nonparametric Statistics

Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from;

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Nonparametric Methods in Statistics with SAS Applications

apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event;

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Nonparametric Methods In Statistics With Sas Applications

apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event;

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Handbook Of Applied Econometrics And Statistical Inference

Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing;

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Handbook Of Applied Econometrics And Statistical Inference

Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing;

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Mixture Modelling for Medical and Health Sciences

Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and;

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Mixture Modelling for Medical and Health Sciences

Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and;

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Higher-Order Growth Curves and Mixture Modeling with Mplus

- The first practical introduction to second-order and growth mixture models using Mplus 8.4 -Introduces simple and complex models;

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Higher-Order Growth Curves and Mixture Modeling with Mplus

- The first practical introduction to second-order and growth mixture models using Mplus 8.4 -Introduces simple and complex models;

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Statistical Tests Of Nonparametric Hypotheses

the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions;

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Estimations And Tests In Change-point Models

of estimation and test in a wide range of models with changes. They include parametric and nonparametric models for samples, series, point processes and;

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Nonparametric Statistics for Non-Statisticians

A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance;

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Data Analysis and Approximate Models

. Forgoing any concept of truth, Data Analysis and Approximate Models: Model Choice, Location-Scale, Analysis of Variance, Nonparametric Regression;

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Advances In Statistical Modeling And Inference

transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage;

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A Primer on Nonparametric Analysis, Volume I

. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric;

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A Primer on Nonparametric Analysis, Volume II

. The method provides an alternative for such cases and is often nearly as powerful as parametric statistics. Another advantage of nonparametric;

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Mixture Model-Based Classification

This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a;

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