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Semiparametric Regression

Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any;

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Semiparametric Regression

Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any;

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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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Themes in Modern Econometrics

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

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Regression And Time Series Model Selection

wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are;

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Regression Modeling: Methods, Theory, and Computation with SAS

regression, random coefficients regression, L1 and q-quantile regression, regression in a spatial domain, ridge regression, semiparametric regression;

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Regression Modeling: Methods, Theory, and Computation with SAS

regression, random coefficients regression, L1 and q-quantile regression, regression in a spatial domain, ridge regression, semiparametric regression;

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Semiparametric Regression for the Social Sciences

An introductory guide to smoothing techniques, semiparametric estimators, and their related methods, this book describes the methodology;

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Handbook of Regression Methods

diverse range of topics, including censored regression, nonlinear regression, generalized linear models, and semiparametric regression;

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Smoothing Splines

smoothing spline ANOVA, extended and generalized smoothing spline ANOVA, vector spline, nonparametric nonlinear regression, semiparametric;

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Smoothing Splines

smoothing spline ANOVA, extended and generalized smoothing spline ANOVA, vector spline, nonparametric nonlinear regression, semiparametric;

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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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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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Regression

The aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between;

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Solutions Manual to accompany Modern Regression Methods, 2e

methods of parameter estimation A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric;

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Multivariate Nonparametric Regression And Visualization

. Exploring the additional applications of nonparametric and semiparametric methods, Multivariate Nonparametric Regression and Visualization features;

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Semiparametric Theory and Missing Data

This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and;

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Nonparametric System Identification

-parametric regression, approximation, and orthogonal expansions, along with new approaches to system identification (including semiparametric;

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Nonparametric System Identification

-parametric regression, approximation, and orthogonal expansions, along with new approaches to system identification (including semiparametric;

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Introduction To Bayesian Econometrics

special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail;

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Nonlinear Time Series

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention;

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Nonlinear Time Series

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention;

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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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The Statistical Analysis of Doubly Truncated Data - With Applications in R

, engineering, and the biomedical sciences to illustrate and highlight the methods described within. Linear regression models for doubly truncated;

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Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life

Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life;

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Introduction to Bayesian Econometrics

semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The new;

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