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Introduction To Nonparametric Regression

This book presents an easy-to-grasp introduction to nonparametric regression. This book's straightforward, step-by-step approach provides;

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Multivariate Nonparametric Regression And Visualization

, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions;

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Local Polynomial Modelling and Its Applications

nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the;

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Nonparametric Regression and Spline Smoothing

Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions;

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Nonparametric Regression and Spline Smoothing

Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions;

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A Distribution-Free Theory of Nonparametric Regression

This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The;

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Nonparametric Regression Methods For Longitudinal Data Analysis

biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed;

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Regression Modeling: Methods, Theory, and Computation with SAS

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques;

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Regression Modeling: Methods, Theory, and Computation with SAS

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques;

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Optimality and adaptivity in nonparametric regression

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Regression: Models, Methods and Applications

Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric;

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Image Processing And Jump Regression Analysis

nonparametric jump regression analysis by outlining procedures that are easy to use, simple to compute, and have proven statistical theory behind them;

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All of Nonparametric Statistics

This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference;

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Nonparametric Statistical Methods Using R

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional;

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Nonparametric Statistical Methods Using R

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers;

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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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Generalized Additive Models

This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These;

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An Introduction to Nonparametric Statistics

An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the;

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Gaussian Process Regression Analysis for Functional Data

Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis;

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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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Nonparametric Econometrics

has evolved over the last five decades. Within this framework this is the first book to discuss the principles of the nonparametric approach;

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Nonparametric Econometrics

has evolved over the last five decades. Within this framework this is the first book to discuss the principles of the nonparametric approach;

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Semiparametic Regression for the Applied Econometrician

This book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples;

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Applied Nonparametric Econometrics

nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to;

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Applied Nonparametric Econometrics

nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to;

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Observed Confidence Levels

and for relatively simple solutions to numerous interesting problems. After an introduction, the book develops the theory and application;

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