Search Results for "foundations-of-linear-and-generalized-linear-models"

Foundations of Linear and Generalized Linear Models

Foundations of Linear and Generalized Linear Models

  • Author: Alan Agresti
  • Publisher: John Wiley & Sons
  • ISBN: 1118730038
  • Category: Mathematics
  • Page: 444
  • View: 8350
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"This book presents an overview of the foundations and the key ideas and results of linear and generalized linear models under one cover. Written by a prolific academic, researcher, and textbook writer, Foundations of Linear and Generalized Linear Modelsis soon to become the gold standard by which all existing textbooks on the topic will be compared. While the emphasis is clearly and succinctly on theoretical underpinnings, applications in "R" are presented when they help to elucidate the content or promote practical model building. Each chapter contains approximately 15-20 exercises, primarily for readers to practice and extend the theory, but, also to assimilate the ideas by doing some data analysis. The carefully crafted models and examples convey basic concepts and do not get mired down in non-trivial considerations. An author-maintained web site includes, among other numerous pedagogical supplements, analyses that parallel the "R" routines from the book in SAS, SPSS and Stata"--

Regression

Regression

Modelle, Methoden und Anwendungen

  • Author: Ludwig Fahrmeir,Thomas Kneib,Stefan Lang
  • Publisher: Springer-Verlag
  • ISBN: 3642018378
  • Category: Business & Economics
  • Page: 502
  • View: 1742
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In dem Band beschreiben die Autoren erstmals klassische Regressionsansätze und moderne nicht- und semiparametrische Methoden in einer integrierten und anwendungsorientierten Form. Um Lesern die Analyse eigener Fragestellungen zu ermöglichen, demonstrieren sie die praktische Anwendung der Konzepte und Methoden anhand ausführlicher Fallstudien. Geeignet für Studierende der Statistik sowie für Wissenschaftler und Praktiker, zum Beispiel in den Wirtschafts- und Sozialwissenschaften, der Bioinformatik und -statistik, Ökonometrie und Epidemiologie.

An Introduction to Categorical Data Analysis

An Introduction to Categorical Data Analysis

  • Author: Alan Agresti
  • Publisher: Wiley
  • ISBN: 1119405262
  • Category: Mathematics
  • Page: 400
  • View: 2568
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A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.

Generalized Linear Models

Generalized Linear Models

with Applications in Engineering and the Sciences

  • Author: Raymond H. Myers,Douglas C. Montgomery,G. Geoffrey Vining,Timothy J. Robinson
  • Publisher: John Wiley & Sons
  • ISBN: 0470556978
  • Category: Mathematics
  • Page: 544
  • View: 4234
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Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities." —Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Maintaining the same nontechnical approach as its predecessor, this update has been thoroughly extended to include the latest developments, relevant computational approaches, and modern examples from the fields of engineering and physical sciences. This new edition maintains its accessible approach to the topic by reviewing the various types of problems that support the use of GLMs and providing an overview of the basic, related concepts such as multiple linear regression, nonlinear regression, least squares, and the maximum likelihood estimation procedure. Incorporating the latest developments, new features of this Second Edition include: A new chapter on random effects and designs for GLMs A thoroughly revised chapter on logistic and Poisson regression, now with additional results on goodness of fit testing, nominal and ordinal responses, and overdispersion A new emphasis on GLM design, with added sections on designs for regression models and optimal designs for nonlinear regression models Expanded discussion of weighted least squares, including examples that illustrate how to estimate the weights Illustrations of R code to perform GLM analysis The authors demonstrate the diverse applications of GLMs through numerous examples, from classical applications in the fields of biology and biopharmaceuticals to more modern examples related to engineering and quality assurance. The Second Edition has been designed to demonstrate the growing computational nature of GLMs, as SAS®, Minitab®, JMP®, and R software packages are used throughout the book to demonstrate fitting and analysis of generalized linear models, perform inference, and conduct diagnostic checking. Numerous figures and screen shots illustrating computer output are provided, and a related FTP site houses supplementary material, including computer commands and additional data sets. Generalized Linear Models, Second Edition is an excellent book for courses on regression analysis and regression modeling at the upper-undergraduate and graduate level. It also serves as a valuable reference for engineers, scientists, and statisticians who must understand and apply GLMs in their work.

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators

  • Author: Tailen Hsing,Randall Eubank
  • Publisher: John Wiley & Sons
  • ISBN: 0470016914
  • Category: Mathematics
  • Page: 480
  • View: 7908
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Functional data is data in the form of curves that is becoming a popular method for interpreting scientific data. Statistical Analysis of Functional Data provides an authoritative account of function data analysis covering its foundations, theory, methodology, and practical implementation. It also contains examples taken from a wide range of disciplines, including finance, medicine, and psychology. The book includes a supporting Web site hosting the real data sets analyzed in the book and related software. Statistical researchers or practitioners analyzing functional data will find this book useful.

Multivariate Density Estimation

Multivariate Density Estimation

Theory, Practice, and Visualization

  • Author: David W. Scott
  • Publisher: John Wiley & Sons
  • ISBN: 1118575482
  • Category: Mathematics
  • Page: 384
  • View: 4664
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Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.

Foundations of Statistical Analyses and Applications with SAS

Foundations of Statistical Analyses and Applications with SAS

  • Author: Michael Falk,Frank Marohn,Bernward Tewes
  • Publisher: Springer Science & Business Media
  • ISBN: 9783764368937
  • Category: Mathematics
  • Page: 402
  • View: 5851
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This book links up the theory of a selection of statistical procedures used in general practice with their application to real world data sets using the statistical software package SAS (Statistical Analysis System). These applications are intended to illustrate the theory and to provide, simultaneously, the ability to use the knowledge effectively and readily in execution.

Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Modeling Techniques

Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Modeling Techniques

  • Author: Edward W. Frees,Richard A. Derrig,Glenn Meyers
  • Publisher: Cambridge University Press
  • ISBN: 1139992317
  • Category: Business & Economics
  • Page: N.A
  • View: 7306
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Predictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data.

Predictive Modeling Applications in Actuarial Science

Predictive Modeling Applications in Actuarial Science

  • Author: Edward W. Frees,Richard A. Derrig,Glenn Meyers
  • Publisher: Cambridge University Press
  • ISBN: 1107029872
  • Category: Business & Economics
  • Page: 544
  • View: 6328
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This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling.

Foundations of Statistical Inference

Foundations of Statistical Inference

Proceedings of the Shoresh Conference 2000

  • Author: Yoel Haitovsky,Hans Rudolf Lerche,Ya'acov Ritov
  • Publisher: Springer Science & Business Media
  • ISBN: 3642574106
  • Category: Mathematics
  • Page: 230
  • View: 1071
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This volume is a collection of papers presented at a conference held in Shoresh Holiday Resort near Jerusalem, Israel, in December 2000 organized by the Israeli Ministry of Science, Culture and Sport. The theme of the conference was "Foundation of Statistical Inference: Applications in the Medical and Social Sciences and in Industry and the Interface of Computer Sciences". The following is a quotation from the Program and Abstract booklet of the conference. "Over the past several decades, the field of statistics has seen tremendous growth and development in theory and methodology. At the same time, the advent of computers has facilitated the use of modern statistics in all branches of science, making statistics even more interdisciplinary than in the past; statistics, thus, has become strongly rooted in all empirical research in the medical, social, and engineering sciences. The abundance of computer programs and the variety of methods available to users brought to light the critical issues of choosing models and, given a data set, the methods most suitable for its analysis. Mathematical statisticians have devoted a great deal of effort to studying the appropriateness of models for various types of data, and defining the conditions under which a particular method work. " In 1985 an international conference with a similar title* was held in Is rael. It provided a platform for a formal debate between the two main schools of thought in Statistics, the Bayesian, and the Frequentists.

R für Dummies

R für Dummies

  • Author: Andrie de Vries,Joris Meys
  • Publisher: John Wiley & Sons
  • ISBN: 3527812520
  • Category: Computers
  • Page: 414
  • View: 7704
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Wollen Sie auch die umfangreichen Möglichkeiten von R nutzen, um Ihre Daten zu analysieren, sind sich aber nicht sicher, ob Sie mit der Programmiersprache wirklich zurechtkommen? Keine Sorge - dieses Buch zeigt Ihnen, wie es geht - selbst wenn Sie keine Vorkenntnisse in der Programmierung oder Statistik haben. Andrie de Vries und Joris Meys zeigen Ihnen Schritt für Schritt und anhand zahlreicher Beispiele, was Sie alles mit R machen können und vor allem wie Sie es machen können. Von den Grundlagen und den ersten Skripten bis hin zu komplexen statistischen Analysen und der Erstellung aussagekräftiger Grafiken. Auch fortgeschrittenere Nutzer finden in diesem Buch viele Tipps und Tricks, die Ihnen die Datenauswertung erleichtern.

Grundbegriffe der Wahrscheinlichkeitstheorie

Grundbegriffe der Wahrscheinlichkeitstheorie

  • Author: K. Hinderer
  • Publisher: Springer-Verlag
  • ISBN: 364280957X
  • Category: Mathematics
  • Page: 248
  • View: 3865
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Relationen und Graphen

Relationen und Graphen

  • Author: Gunther Schmidt,Thomas Ströhlein
  • Publisher: Springer-Verlag
  • ISBN: 3642836089
  • Category: Mathematics
  • Page: 306
  • View: 914
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Dieses Buch gibt eine neuartige systematische Darstellung der Diskreten Mathematik; sie orientiert sich an Methoden der Relationenalgebra. Ähnlich wie man es sonst nur für die weit entwickelte Analysis im kontinuierlichen Fall und die Matrizenrechnung gewohnt ist, stellt dieses Buch auch für die Behandlung diskreter Probleme geeignete Techniken und Hilfsmittel sowie eine einheitliche Theorie bereit. Die einzelnen Kapitel beginnen jeweils mit anschaulichen und motivierenden Beispielen und behandeln anschließend den Stoff in mathematischer Strenge. Es folgen jeweils praktische Anwendungen. Diese entstammen der Semantik der Programmierung, der Programmverifikation, dem Datenbankbereich, der Spieltheorie oder der Theorie der Zuordnungen und Überdeckungen aus der Graphentheorie; sie reichen aber auch bis zu rein mathematischen "Anwendungen" wie der transfiniten Induktion. Im Anhang ist dem Buch eine Einführung in die Boolesche Algebra und in die Axiomatik der Relationenalgebra beigegeben, sowie ein Abriß der Fixpunkt- und Antimorphismen-Theorie.

Programmieren mit R

Programmieren mit R

  • Author: Uwe Ligges
  • Publisher: Springer-Verlag
  • ISBN: 3540267328
  • Category: Mathematics
  • Page: 237
  • View: 4815
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R ist eine objekt-orientierte und interpretierte Sprache und Programmierumgebung für Datenanalyse und Grafik - frei erhältlich unter der GPL. Ziel dieses Buches ist es, nicht nur ausführlich in die Grundlagen der Sprache R einzuführen, sondern auch ein Verständnis der Struktur der Sprache zu vermitteln. Leicht können so eigene Methoden umgesetzt, Objektklassen definiert und ganze Pakete aus Funktionen und zugehöriger Dokumentation zusammengestellt werden. Die enormen Grafikfähigkeiten von R werden detailliert beschrieben. Das Buch richtet sich an alle, die R als flexibles Werkzeug zur Datenenalyse und -visualisierung einsetzen möchten: Studierende, die Daten in Projekten oder für ihre Diplomarbeit analysieren möchten, Forschende, die neue Methoden ausprobieren möchten, und diejenigen, die in der Wirtschaft täglich Daten aufbereiten, analysieren und anderen in komprimierter Form präsentieren.

Die Kunst des professionellen Schreibens

Die Kunst des professionellen Schreibens

ein Leitfaden für die Geistes- und Sozialwissenschaften

  • Author: Howard Saul Becker
  • Publisher: N.A
  • ISBN: 9783593367101
  • Category: Academic writing
  • Page: 223
  • View: 4104
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R in a Nutshell

R in a Nutshell

  • Author: Joseph Adler
  • Publisher: O'Reilly Germany
  • ISBN: 3897216507
  • Category: Computers
  • Page: 768
  • View: 6723
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Wozu sollte man R lernen? Da gibt es viele Gründe: Weil man damit natürlich ganz andere Möglichkeiten hat als mit einer Tabellenkalkulation wie Excel, aber auch mehr Spielraum als mit gängiger Statistiksoftware wie SPSS und SAS. Anders als bei diesen Programmen hat man nämlich direkten Zugriff auf dieselbe, vollwertige Programmiersprache, mit der die fertigen Analyse- und Visualisierungsmethoden realisiert sind – so lassen sich nahtlos eigene Algorithmen integrieren und komplexe Arbeitsabläufe realisieren. Und nicht zuletzt, weil R offen gegenüber beliebigen Datenquellen ist, von der einfachen Textdatei über binäre Fremdformate bis hin zu den ganz großen relationalen Datenbanken. Zudem ist R Open Source und erobert momentan von der universitären Welt aus die professionelle Statistik. R kann viel. Und Sie können viel mit R machen – wenn Sie wissen, wie es geht. Willkommen in der R-Welt: Installieren Sie R und stöbern Sie in Ihrem gut bestückten Werkzeugkasten: Sie haben eine Konsole und eine grafische Benutzeroberfläche, unzählige vordefinierte Analyse- und Visualisierungsoperationen – und Pakete, Pakete, Pakete. Für quasi jeden statistischen Anwendungsbereich können Sie sich aus dem reichen Schatz der R-Community bedienen. Sprechen Sie R! Sie müssen Syntax und Grammatik von R nicht lernen – wie im Auslandsurlaub kommen Sie auch hier gut mit ein paar aufgeschnappten Brocken aus. Aber es lohnt sich: Wenn Sie wissen, was es mit R-Objekten auf sich hat, wie Sie eigene Funktionen schreiben und Ihre eigenen Pakete schnüren, sind Sie bei der Analyse Ihrer Daten noch flexibler und effektiver. Datenanalyse und Statistik in der Praxis: Anhand unzähliger Beispiele aus Medizin, Wirtschaft, Sport und Bioinformatik lernen Sie, wie Sie Daten aufbereiten, mithilfe der Grafikfunktionen des lattice-Pakets darstellen, statistische Tests durchführen und Modelle anpassen. Danach werden Ihnen Ihre Daten nichts mehr verheimlichen.

Elementare Wahrscheinlichkeitstheorie und stochastische Prozesse

Elementare Wahrscheinlichkeitstheorie und stochastische Prozesse

  • Author: Kai L. Chung
  • Publisher: Springer-Verlag
  • ISBN: 3642670334
  • Category: Mathematics
  • Page: 346
  • View: 6262
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Aus den Besprechungen: "Unter den zahlreichen Einführungen in die Wahrscheinlichkeitsrechnung bildet dieses Buch eine erfreuliche Ausnahme. Der Stil einer lebendigen Vorlesung ist über Niederschrift und Übersetzung hinweg erhalten geblieben. In jedes Kapitel wird sehr anschaulich eingeführt. Sinn und Nützlichkeit der mathematischen Formulierungen werden den Lesern nahegebracht. Die wichtigsten Zusammenhänge sind als mathematische Sätze klar formuliert." #FREQUENZ#1

Systemintegration

Systemintegration

Vom Transistor zur großintegrierten Schaltung

  • Author: Kurt Hoffmann
  • Publisher: Walter de Gruyter
  • ISBN: 3486720007
  • Category: Technology & Engineering
  • Page: 621
  • View: 4112
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In dem vorliegenden Lehrbuch wird zunächst Wissen über das grundsätzliche Verhalten der verschiedensten Bauelemente integrierter Schaltungen vermittelt. Erst dann werden die wesentlichen Schaltungstechniken für den Entwurf von digitalen und analogen CMOS- und BICMOS-Schaltungen vorgestellt. Dem Autor gelingt es schlüssig, den weiten Bogen von den Grundlagen der Physik bis zu tatsächlichen Anwendungen und der Produktion von Halbleiterschaltungen zu spannen und so einen umfassenden Überblick über den Designprozess in der Mikroelektronik zu geben.

Mathematical and Numerical Foundations of Turbulence Models and Applications

Mathematical and Numerical Foundations of Turbulence Models and Applications

  • Author: Tomás Chacón Rebollo,Roger Lewandowski
  • Publisher: Springer
  • ISBN: 1493904558
  • Category: Mathematics
  • Page: 517
  • View: 6290
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With applications to climate, technology, and industry, the modeling and numerical simulation of turbulent flows are rich with history and modern relevance. The complexity of the problems that arise in the study of turbulence requires tools from various scientific disciplines, including mathematics, physics, engineering and computer science. Authored by two experts in the area with a long history of collaboration, this monograph provides a current, detailed look at several turbulence models from both the theoretical and numerical perspectives. The k-epsilon, large-eddy simulation and other models are rigorously derived and their performance is analyzed using benchmark simulations for real-world turbulent flows. Mathematical and Numerical Foundations of Turbulence Models and Applications is an ideal reference for students in applied mathematics and engineering, as well as researchers in mathematical and numerical fluid dynamics. It is also a valuable resource for advanced graduate students in fluid dynamics, engineers, physical oceanographers, meteorologists and climatologists.

Analytical Foundations of Marxian Economic Theory

Analytical Foundations of Marxian Economic Theory

  • Author: John E. Roemer
  • Publisher: Cambridge University Press
  • ISBN: 9780521347754
  • Category: Business & Economics
  • Page: 220
  • View: 7033
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This book gives a rigorous view of classical Marxian economic theory by presenting specific analytic models.