Angebote zu "Regression" (171 Treffer)

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Cook: Applied Regression Computing Graphics
231,89 € *
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Erscheinungsdatum: 23.07.1999, Medium: Buch, Einband: Gebunden, Titel: Applied Regression Computing Graphics, Autor: Cook // Weisberg, Verlag: John Wiley & Sons, Sprache: Englisch, Schlagworte: MATHEMATICS // Applied, Rubrik: Mathematik // Sonstiges, Seiten: 632, Informationen: HC gerader Rücken kaschiert, Gewicht: 1106 gr, Verkäufer: averdo

Anbieter: averdo
Stand: 03.06.2020
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Regression Graphics
152,99 € *
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Regression Graphics ab 152.99 € als pdf eBook: Ideas for Studying Regressions Through Graphics. Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik,

Anbieter: hugendubel
Stand: 03.06.2020
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Regression Through Graphics
198,99 € *
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Regression Through Graphics ab 198.99 € als gebundene Ausgabe: . Aus dem Bereich: Bücher, Wissenschaft, Mathematik,

Anbieter: hugendubel
Stand: 03.06.2020
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Applied Regression Computing Graphics
206,99 € *
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Applied Regression Computing Graphics ab 206.99 € als gebundene Ausgabe: . Aus dem Bereich: Bücher, Wissenschaft, Mathematik,

Anbieter: hugendubel
Stand: 03.06.2020
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Applied Regression Including Computing and Grap...
158,99 € *
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Applied Regression Including Computing and Graphics ab 158.99 € als pdf eBook: . Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik,

Anbieter: hugendubel
Stand: 03.06.2020
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ggplot2
53,49 € *
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This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to: produce handsome, publication-quality plots with automatic legends created from the plot specification superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.

Anbieter: buecher
Stand: 03.06.2020
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ggplot2
54,99 € *
ggf. zzgl. Versand

This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to: produce handsome, publication-quality plots with automatic legends created from the plot specification superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.

Anbieter: buecher
Stand: 03.06.2020
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An Introduction to Statistical Learning
50,99 € *
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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Anbieter: buecher
Stand: 03.06.2020
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An Introduction to Statistical Learning
50,99 € *
ggf. zzgl. Versand

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Anbieter: buecher
Stand: 03.06.2020
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