2010-01-05 18:43:28| 分类: R&Bioconductor | 标签: |举报 |字号大中小 订阅
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[bib | Discount Info | Publisher Info ] This is also called the “White Book”, and introduced S version 3, which added structures to facilitate statistical modeling in S. |
[bib | Discount Info | Publisher Info | http://cm.bell-labs.com/cm/ms/departments/sia/Sbook/ ] This “Green Book” describes version 4 of S, a major revision of S designed by John Chambers to improve its usefulness at every stage of the programming process. |
[bib | Discount Info | Publisher Info | http://www.stats.ox.ac.uk/pub/MASS4/ ] |
[bib | Discount Info | Publisher Info | http://www.stats.ox.ac.uk/pub/MASS3/Sprog/ ] This provides an in-depth guide to writing software in the S language which forms the basis of both the commercial S-Plus and the Open Source R da |
[bib | Discount Info | Publisher Info | http://www.stat.Berkeley.EDU/users/statlabs/ ] Integrates theory of statistics with the practice of statistics through a collection of case studies (“labs”), and uses R to analyze the da |
[bib | Discount Info | Publisher Info ] A comprehensive guide to the use of the `nlme' package for linear and nonlinear mixed-effects models. |
[bib | Discount Info | Publisher Info | http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/RmS ] |
[bib ] This book, written in Spanish, is oriented to researchers interested in applying multivariate analysis techniques to real processes. It combines the theoretical basis with applied examples coded in R. |
[bib | http://socserv.socsci.mcmaster.ca/jfox/Books/Companion/index.html ] A companion book to a text or course on applied regression (such as “Applied Regression, Linear Models, and Related Methods” by the same author). It introduces S, and concentrates on how to use linear and generalized-linear models in S while assuming familiarity with the statistical methodology. |
[bib | Discount Info | Publisher Info | http://www.biostat.ku.dk/~pd/ISwR.html ] |
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[bib | Publisher Info | http://wwwmaths.anu.edu.au/~johnm/r-book.html ] |
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[bib | Discount Info | Publisher Info | http://www.maths.bath.ac.uk/~jjf23/LMR/ ] The book focuses on the practice of regression and analysis of variance. It clearly demonstrates the different methods available and in which situations each on |
[bib | Discount Info | Publisher Info | http://astro.temple.edu/~rmh/HH ] |
[bib | Discount Info | Publisher Info | http://wiener.math.csi.cuny.edu/UsingR/ ] |
[bib | Discount Info | Publisher Info | http://www.cs.rhul.ac.uk/home/fionn/ ] |
[bib | Discount Info | Publisher Info | http://www.stat.auckland.ac.nz/~paul/RGraphics/rgraphics.html ] |
[bib | Publisher Info | http://www.bio.ic.ac.uk/research/crawley/statistics/ ] |
[bib | Discount Info | Publisher Info | http://biostatistics.iop.kcl.ac.uk/publications/everitt/ ] |
[bib | Discount Info | Publisher Info ] Computational Genome Analysis: An Introduction presents the foundations of key p roblems in computational molecular biology and bioinformatics. It focuses on com putational and statistical principles applied to genomes, and introduces the mat hematics and statistics that are crucial for understanding these applications. A ll computations are done with R. |
[bib | Discount Info | Publisher Info ] This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including imp |
[bib | Discount Info | Publisher Info ] This is a book for statistical practitioners, particularly those who design and analyze studies for survival and event history da |
[bib | Discount Info | Publisher Info | http://cran.r-project.org/src/contrib/Descriptions/HSAUR.html ] With emphasis on the use of R and the interpretation of results rather than the theory behind the methods, this book addresses particular statistical techniques and demonstrates how they can be applied to on |
[bib | Discount Info | Publisher Info | http://www.maths.bath.ac.uk/~jjf23/ELM/ ] This book surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author's treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the da |
[bib | Discount Info | Publisher Info | http://www.fp.vslib.cz/kap/picek/robust/ ] |
[bib | Discount Info | Publisher Info | http://cran.r-project.org/src/contrib/Descriptions/gamair.html ] This book imparts a thorough understanding of the theory and practical applications of GAMs and related advanced models, enabling informed use of these very flexible tools. The author bases his approach on a framework of penalized regression splines, and builds a well- grounded foundation through motivating chapters on linear and generalized linear models. While firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. The treatment is rich with practical examples, and it includes an entire chapter on the analysis of real da |
[bib | Discount Info | Publisher Info ] The book encompasses seasonal unit roots, fractional integration, coping with structural breaks, and inference in cointegrated vector autoregressive models. |
[bib | Discount Info | Publisher Info ] This book provides a broad introduction to the subject of environmental space-time processes, addressing the role of uncertainty. It covers a spectrum of technical matters from measurement to environmental epidemiology to risk assessment. It showcases non-stationary vector-valued processes, while treating stationarity as a special case. In particular, with members of their research group the authors developed within a hierarchical Bayesian framework, the new statistical approaches presented in the book for analyzing, modeling, and monitoring environmental spatio-temporal processes. Furthermore they indicate new directions for development. |
[bib | Discount Info | Publisher Info ] Geostatistics is concerned with estimation and prediction problems for spatially continuous phenomena, using da |
[bib | Discount Info | Publisher Info ] This book integrates a wide variety of da |
[bib | Discount Info | Publisher Info ] This book provides a detailed account of the theoretical foundations of proposed multiple testing methods and illustrates their application to a range of testing problems in genomics. |
[bib | Publisher Info | http://www.statistik.uni-dortmund.de/~ligges/PmitR/ ] R ist eine objekt-orientierte und interpretierte Sprache und Programmierumgebung für Datenanalyse und Grafik - frei erh?ltlich unter der GPL. Das Buch führt in die Grundlagen der Sprache R ein und vermittelt ein umfassendes Verst?ndnis der Sprachstruktur. Die enormen Grafikf?higkeiten von R werden detailliert beschrieben. Der Leser kann leicht eigene Methoden umsetzen, Objektklassen definieren und ganze Pakete aus Funktionen und zugeh?riger Dokumentation zusammenstellen. Ob Diplomarbeit, Forschungsprojekte oder Wirtschaftsdaten, das Buch unterstützt alle, die R als flexibles Werkzeug zur Datenanalyse und -visualisierung einsetzen m?chten. |
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[bib | Discount Info | Publisher Info ] Introduction to Bayesian Statistics and Estimation for Social Scientists covers the complete process of Bayesian statistical analysis in great detail from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research-including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models-and it thoroughly develops each real-da |
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