Extended Model Formulas in R: Multiple Parts and Multiple Responses

Model formulas are the standard approach for specifying the variables in statistical models in the S language. Although being eminently useful in an extremely wide class of applications, they have certain limitations including being confined to single responses and not providing convenient support f...

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Bibliographic Details
Main Authors: Yves Croissant, Achim Zeileis
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2010-10-01
Series:Journal of Statistical Software
Subjects:
R.
Online Access:http://www.jstatsoft.org/v34/i01/paper
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spelling doaj-c545f6d7d69c4e93893b642aa6c881dd2020-11-25T01:27:40ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602010-10-013401Extended Model Formulas in R: Multiple Parts and Multiple ResponsesYves CroissantAchim ZeileisModel formulas are the standard approach for specifying the variables in statistical models in the S language. Although being eminently useful in an extremely wide class of applications, they have certain limitations including being confined to single responses and not providing convenient support for processing formulas with multiple parts. The latter is relevant for models with two or more sets of variables, e.g., different equations for different model parameters (such as mean and dispersion), regressors and instruments in instrumental variable regressions, two-part models such as hurdle models, or alternative-specific and individual-specific variables in choice models among many others. The R package Formula addresses these two problems by providing a new class “Formula” (inheriting from “formula”) that accepts an additional formula operator | separating multiple parts and by allowing all formula operators (including the new |) on the left-hand side to support multiple responses.http://www.jstatsoft.org/v34/i01/paperformula processingmodel framemodel matrixR.
collection DOAJ
language English
format Article
sources DOAJ
author Yves Croissant
Achim Zeileis
spellingShingle Yves Croissant
Achim Zeileis
Extended Model Formulas in R: Multiple Parts and Multiple Responses
Journal of Statistical Software
formula processing
model frame
model matrix
R.
author_facet Yves Croissant
Achim Zeileis
author_sort Yves Croissant
title Extended Model Formulas in R: Multiple Parts and Multiple Responses
title_short Extended Model Formulas in R: Multiple Parts and Multiple Responses
title_full Extended Model Formulas in R: Multiple Parts and Multiple Responses
title_fullStr Extended Model Formulas in R: Multiple Parts and Multiple Responses
title_full_unstemmed Extended Model Formulas in R: Multiple Parts and Multiple Responses
title_sort extended model formulas in r: multiple parts and multiple responses
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2010-10-01
description Model formulas are the standard approach for specifying the variables in statistical models in the S language. Although being eminently useful in an extremely wide class of applications, they have certain limitations including being confined to single responses and not providing convenient support for processing formulas with multiple parts. The latter is relevant for models with two or more sets of variables, e.g., different equations for different model parameters (such as mean and dispersion), regressors and instruments in instrumental variable regressions, two-part models such as hurdle models, or alternative-specific and individual-specific variables in choice models among many others. The R package Formula addresses these two problems by providing a new class “Formula” (inheriting from “formula”) that accepts an additional formula operator | separating multiple parts and by allowing all formula operators (including the new |) on the left-hand side to support multiple responses.
topic formula processing
model frame
model matrix
R.
url http://www.jstatsoft.org/v34/i01/paper
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