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Title:

From Spider-Man to Hero — Archetypal Analysis in R

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Archetypal analysis has the aim to represent observations in a multivariate data setas convex combinations of extremal points. This approach was introduced by Cutler andBreiman (1994); they dened the concrete problem, laid out the theoretical foundationsand presented an algorithm written in Fortran. In this paper we present the R packagearchetyp...

Archetypal analysis has the aim to represent observations in a multivariate data setas convex combinations of extremal points. This approach was introduced by Cutler andBreiman (1994); they dened the concrete problem, laid out the theoretical foundationsand presented an algorithm written in Fortran. In this paper we present the R packagearchetypes which is available on the Comprehensive R Archive Network. The packageprovides an implementation of the archetypal analysis algorithm within R and dierentexploratory tools to analyze the algorithm during its execution and its nal result. Theapplication of the package is demonstrated on two examples. Minimize

Publisher:

University of California, Los Angeles

Year of Publication:

2009-04-01T00:00:00Z

Source:

Journal of Statistical Software, Vol 30, Iss 8 (2009)

Journal of Statistical Software, Vol 30, Iss 8 (2009) Minimize

Document Type:

article

Language:

English

Subjects:

archetypal analysis ; convex hull ; R ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H ; LCC:Statistics ; ...

archetypal analysis ; convex hull ; R ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H ; DOAJ:Statistics ; DOAJ:Mathematics and Statistics ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H ; LCC:Statistics ; LCC:HA1-4737 ; LCC:Social Sciences ; LCC:H Minimize

DDC:

300 Social sciences *(computed)*

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CC BY

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Title:

From Spider-Man to Hero - Archetypal Analysis in R

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Archetypal analysis has the aim to represent observations in a multivariate data set as convex combinations of extremal points. This approach was introduced by Cutler and Breiman (1994); they defined the concrete problem, laid out the theoretical foundations and presented an algorithm written in Fortran. In this paper we present the R package ar...

Archetypal analysis has the aim to represent observations in a multivariate data set as convex combinations of extremal points. This approach was introduced by Cutler and Breiman (1994); they defined the concrete problem, laid out the theoretical foundations and presented an algorithm written in Fortran. In this paper we present the R package archetypes which is available on the Comprehensive R Archive Network. The package provides an implementation of the archetypal analysis algorithm within R and different exploratory tools to analyze the algorithm during its execution and its final result. The application of the package is demonstrated on two examples. Minimize

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article

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Suggests MASS, vcd, mlbench, ggplot2

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Description The main function archetypes implements a framework for archetypal analysis supporting arbitary problem solving mechanisms for the different conceputal parts of the algorithm.

Description The main function archetypes implements a framework for archetypal analysis supporting arbitary problem solving mechanisms for the different conceputal parts of the algorithm. Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2011-11-13

Source:

http://cran.at.r-project.org/web/packages/archetypes/archetypes.pdf

http://cran.at.r-project.org/web/packages/archetypes/archetypes.pdf Minimize

Document Type:

text

Language:

en

Subjects:

Depends methods ; stats ; modeltools ; nnls (> = 1.1

Depends methods ; stats ; modeltools ; nnls (> = 1.1 Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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License GPL (> = 2)

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Description The benchmark package provides a toolbox for setup,execution and analysis of benchmark experiments. Main focus is the analysis of data accumulating during the execution-- one primary objective is the statistical correct computation of the candidate algorithms ' order.

Description The benchmark package provides a toolbox for setup,execution and analysis of benchmark experiments. Main focus is the analysis of data accumulating during the execution-- one primary objective is the statistical correct computation of the candidate algorithms ' order. Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2011-06-26

Source:

http://cran.at.r-project.org/web/packages/benchmark/benchmark.pdf

http://cran.at.r-project.org/web/packages/benchmark/benchmark.pdf Minimize

Document Type:

text

Language:

en

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Depends utils ; proto ; ggplot2 ; reshape ; relations Suggests coin ; multcomp ; lme4 ; e1071 ; entropy ; archetypes ; Rgraphviz

Depends utils ; proto ; ggplot2 ; reshape ; relations Suggests coin ; multcomp ; lme4 ; e1071 ; entropy ; archetypes ; Rgraphviz Minimize

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

Weighted and Robust Archetypal Analysis

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Archetypal analysis represents observations in a multivariate data set as convex combinations of a few extremal points lying on the boundary of the convex hull. Data points which vary from the majority have great influence on the solution; in fact one outlier can break down the archetype solution. This paper adapts the original algorithm to be a...

Archetypal analysis represents observations in a multivariate data set as convex combinations of a few extremal points lying on the boundary of the convex hull. Data points which vary from the majority have great influence on the solution; in fact one outlier can break down the archetype solution. This paper adapts the original algorithm to be a robust M-estimator and presents an iteratively reweighted least squares fitting algorithm. As required first step, the weighted archetypal problem is formulated and solved. The algorithm is demonstrated using both an artificial and a real world example. 1 Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2013-12-05

Source:

http://epub.ub.uni-muenchen.de/11498/1/tr82.pdf

http://epub.ub.uni-muenchen.de/11498/1/tr82.pdf Minimize

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text

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en

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Metadata may be used without restrictions as long as the oai identifier remains attached to it.

Metadata may be used without restrictions as long as the oai identifier remains attached to it. Minimize

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Title:

benchmark analysis toolbox

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First steps toward a comprehensive

First steps toward a comprehensive Minimize

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The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2013-08-21

Source:

http://epub.ub.uni-muenchen.de/3206/1/tr026.pdf

http://epub.ub.uni-muenchen.de/3206/1/tr026.pdf Minimize

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text

Language:

en

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Compstat 2008-Proceedings in Computational Statistics

Compstat 2008-Proceedings in Computational Statistics Minimize

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Title:

Having the Second Leg at Home - Advantage in the UEFA Champions League Knockout Phase?

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In soccer knockout ties, which are played in a two-legged format, the team having the return match at home is usually seen as advantaged. For checking this common belief, we analyzed matches of the UEFA Champions League knockout phase since 1994/1995. It is shown that the observed differences in frequencies of winning between teams first playing...

In soccer knockout ties, which are played in a two-legged format, the team having the return match at home is usually seen as advantaged. For checking this common belief, we analyzed matches of the UEFA Champions League knockout phase since 1994/1995. It is shown that the observed differences in frequencies of winning between teams first playing away and those which are first playing at home can be completely explained by their performances on the group stage andâ€”more importantlyâ€”by the teams' general strength. ; Other Sport, home field advantage, knockout matches, logit model, soccer, UEFA Champions League Minimize

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http://www.stat.uni-muenchen.de Spider-Man, the Child, and the Trickster 1 – Archetypal Analysis in R

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Archetypal analysis has the aim to represent observations in a multivariate data set as convex combinations of extremal points. This approach was introduced by Cutler and Breiman (1994); they defined the concrete problem, laid out the theoretical foundations and presented an algorithm written in Fortran, which is available on request. In this pa...

Archetypal analysis has the aim to represent observations in a multivariate data set as convex combinations of extremal points. This approach was introduced by Cutler and Breiman (1994); they defined the concrete problem, laid out the theoretical foundations and presented an algorithm written in Fortran, which is available on request. In this paper we present the R package archetypes which is available on the Comprehensive R Archive Network. The package provides an implementation of the archetypal analysis algorithm within R and different exploratory tools to analyze the algorithm during its execution and its final result. The application of the package is demonstrated on two examples. Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2010-03-06

Source:

http://epub.ub.uni-muenchen.de/8270/1/tr44.pdf

http://epub.ub.uni-muenchen.de/8270/1/tr44.pdf Minimize

Document Type:

text

Language:

en

Subjects:

archetypal analysis ; convex hull ; R

archetypal analysis ; convex hull ; R Minimize

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Collate

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Description The main function archetypes implements a framework for archetypal analysis supporting arbitary problem solving mechanisms for the different conceputal parts of the algorithm.

Description The main function archetypes implements a framework for archetypal analysis supporting arbitary problem solving mechanisms for the different conceputal parts of the algorithm. Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2013-07-24

Source:

http://cran.at.r-project.org/web/packages/archetypes/archetypes.pdf

http://cran.at.r-project.org/web/packages/archetypes/archetypes.pdf Minimize

Document Type:

text

Language:

en

Subjects:

Depends methods ; stats ; modeltools ; nnls (> = 1.1) Suggests MASS ; vcd ; mlbench ; ggplot2

Depends methods ; stats ; modeltools ; nnls (> = 1.1) Suggests MASS ; vcd ; mlbench ; ggplot2 Minimize

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Title:

From Spider-Man to Hero – Archetypal Analysis in R

Author:

Description:

Archetypal analysis has the aim to represent observations in a multivariate data set as convex combinations of extremal points. This approach was introduced by Cutler and Breiman (1994); they defined the concrete problem, laid out the theoretical foundations and presented an algorithm written in Fortran. In this paper we present the R package ar...

Archetypal analysis has the aim to represent observations in a multivariate data set as convex combinations of extremal points. This approach was introduced by Cutler and Breiman (1994); they defined the concrete problem, laid out the theoretical foundations and presented an algorithm written in Fortran. In this paper we present the R package archetypes which is available on the Comprehensive R Archive Network. The package provides an implementation of the archetypal analysis algorithm within R and different exploratory tools to analyze the algorithm during its execution and its final result. The application of the package is demonstrated on two examples. Minimize

Contributors:

The Pennsylvania State University CiteSeerX Archives

Year of Publication:

2010-12-19

Source:

http://www.jstatsoft.org/v30/i08/paper/

http://www.jstatsoft.org/v30/i08/paper/ Minimize

Document Type:

text

Language:

en

Subjects:

archetypal analysis ; convex hull ; R

archetypal analysis ; convex hull ; R Minimize

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