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Methods And Applications Of Linear Models

thoroughly updated book, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition features innovative;

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Simultaneous Inference in Regression

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;

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Simultaneous Inference in Regression

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;

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Nonlinear Statistical Models

models, multivariate regression models, and simultaneous equation models. Methods are illustrated with worked examples, complete with figures;

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Methods and Applications of Longitudinal Data Analysis

, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical;

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Economic Applications of Quantile Regression

Quantile regression has emerged as an essential statistical tool of contemporary empirical economics and biostatistics. Complementing;

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Regression: Models, Methods and Applications

regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal;

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Economic Applications of Quantile Regression

Quantile regression has emerged as an essential statistical tool of contemporary empirical economics and biostatistics. Complementing;

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Robust Nonlinear Regression

Applications using R covers a variety of theories and applications of nonlinear robust regression. It discusses both parts of the classic and robust;

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Partially Linear Models

In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing;

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Regression Models as a Tool in Medical Research

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the;

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Regression Models As A Tool In Medical Research

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the;

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Regression Models For Time Series Analysis

is not appropriate. This book introduces the reader to newer developments and more diverse regression models and methods for time series analysis;

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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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First Hitting Time Regression Models

This book aims to promote regression methods for analyzing lifetime (or time-to-event) data that are based on a representation of the;

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Artificial Intelligence for Automated Pricing Based on Product Descriptions

and deep learning methods for pricing, including from regression methods to hybrid and ensemble methods. The computational experiments are;

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Handbook of Probabilistic Models

. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications;

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Nonparametric Statistical Methods Using R

, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters;

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Nonparametric Statistical Methods Using R

two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event;

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Theory Of Preliminary Test And Stein-Type Estimation With Applications

various topics, including: Simple linear model; ANOVA; parallelism model; multiple regression model with non-stochastic and stochastic;

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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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Handbook of Regression Methods

Handbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook;

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Regression And Time Series Model Selection

selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including;

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Applied Economic Forecasting using Time Series Methods

specific regression topics relevant for forecasting, such as model specification errors, dynamic models and their predictive properties as well as;

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Confidence Intervals in Generalized Regression Models

regression model, generalized linear model (GLIM), logistic regression model, Poisson regression model, multinomial regression model, and Cox;

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Confidence Intervals in Generalized Regression Models

regression model, generalized linear model (GLIM), logistic regression model, Poisson regression model, multinomial regression model, and Cox;

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Applied Regression Analysis and Generalized Linear Models

Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the;

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