<p>The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.</p>

Multivariate Statistical Modelling Based on Generalized Linear Models (Springer Series in Statistics)

Business & Money

Fahrmeir, Ludwig

Tutz, Gerhard

Education & Reference

Springer

<p>This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods, which provide excellent tools for prediction and the handling of both nominal and ordered categorical predictors. The book is accompanied an R package that contains data sets and code for all the examples.</p>

Regression for Categorical Data (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 34)

Science & Math

Mathematics

Cambridge University Press

Economics

<p>This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book. <br></p>

Modeling Discrete Time-to-Event Data (Springer Series in Statistics)

Computers & Technology

Schmid, Matthias

Software

Statistik. Der Weg zur Datenanalyse.

Künstler, Rita

Pigeot, Iris

Springer, Berlin

Statistik. Der Weg zur Datenanalyse (Springer-Lehrbuch)

Springer, Verlag

<p><div> <p>Dieses Lehrbuch liefert eine umfassende Darstellung der deskriptiven und induktiven Statistik sowie moderner Methoden der explorativen Datenanalyse. Dabei stehen inhaltliche Motivation, Interpretation und Verständnis der Methoden im Vordergrund. Unterstützt werden diese durch zahlreiche Grafiken und Anwendungsbeispiele, die auf realen Daten basieren, sowie passende exemplarische <i>R</i>-Codes und Datensätze. Die im Buch beschriebenen Ergebnisse können außerdem anhand der online zur Verfügung stehenden Materialien reproduziert sowie um eigene Analysen ergänzt werden. Eine kurze Einführung in die freie Programmiersprache <i>R</i> ist ebenfalls enthalten. Hervorhebungen erhöhen die Lesbarkeit und Übersichtlichkeit. Das Buch eignet sich als vorlesungsbegleitende Lektüre, aber auch zum Selbststudium.</p> </div> <div>Für die 9. Auflage wurde das Buch inhaltlich überarbeitet und ergänzt. Leserinnen und Leser erhalten nun in der Springer-Nature-Flashcards-App zusätzlich kostenfreien Zugriff auf über 100 exklusive Lernfragen, mit denen sie ihr Wissen überprüfen können.<br /></div></p>

Statistik: Der Weg zur Datenanalyse (German Edition)

Heumann, Christian

Springer Spektrum

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