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Nonparametric Regression Methods For Longitudinal Data Analysis

nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling;

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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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Methods and Applications of Longitudinal Data Analysis

Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical;

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Nonparametric Models for Longitudinal Data

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric;

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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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Multivariate Nonparametric Regression And Visualization

readers to utilize throughout the book Multivariate Nonparametric Regression and Visualization is an ideal textbook for upper-undergraduate and;

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Survivorship Analysis for Clinical Studies

Written for clinicians and biostatisticians, describes nonparametric and quasiparametric (regression) methods of analyzing survivorship;

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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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Nonparametric Models for Longitudinal Data

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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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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Introduction To Nonparametric Regression

. Practitioners who rely on nonparametric regression for analyzing data in the physical, biological, and social sciences, as well as in finance and;

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The SAGE Handbook of Regression Analysis and Causal Inference

longitudinal data with an emphasis on causal analysis and provides readers with an introduction to and exploration of a large range of techniques.;

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Longitudinal Data Analysis

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight;

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Nonparametric Statistical Methods Using R

cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data;

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Nonparametric Statistical Methods Using R

for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust;

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Frontiers In Statistics

methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re;

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Frontiers In Statistics

methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re;

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Applied Nonparametric Econometrics

advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to;

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Applied Nonparametric Econometrics

advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to;

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Handbook of Regression Analysis With Applications in R

and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians.;

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Practical Statistical Methods

an extensive statistical background. In addition to nonparametric methods, it covers methods for discrete and continuous data. Omitting;

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Practical Statistical Methods

an extensive statistical background. In addition to nonparametric methods, it covers methods for discrete and continuous data. Omitting;

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Statistical Methods for Engineers and Scientists

emphasizes the analysis of variance, regression analysis and the use of Statistical Analysis System computer programs. This edition: discusses modern;

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Statistical Methods for Engineers and Scientists

emphasizes the analysis of variance, regression analysis and the use of Statistical Analysis System computer programs. This edition: discusses modern;

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