The Calculus of M-Estimation in R with geex
M-estimation, or estimating equation, methods are widely applicable for point estimation and asymptotic inference. In this paper, we present an R package that can find roots and compute the empirical sandwich variance estimator for any set of user-specified, unbiased estimating equations. Examples f...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Foundation for Open Access Statistics
2020-02-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/3470 |
| _version_ | 1818263649653882880 |
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| author | Bradley C. Saul Michael G. Hudgens |
| author_facet | Bradley C. Saul Michael G. Hudgens |
| author_sort | Bradley C. Saul |
| collection | DOAJ |
| description | M-estimation, or estimating equation, methods are widely applicable for point estimation and asymptotic inference. In this paper, we present an R package that can find roots and compute the empirical sandwich variance estimator for any set of user-specified, unbiased estimating equations. Examples from the M-estimation primer by Stefanski and Boos (2002) demonstrate use of the software. The package also includes a framework for finite sample, heteroscedastic, and autocorrelation variance corrections, and a website with an extensive collection of tutorials. |
| first_indexed | 2024-12-12T19:22:23Z |
| format | Article |
| id | doaj.art-eecd8647dd5e488089b990661a66e96c |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-12-12T19:22:23Z |
| publishDate | 2020-02-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-eecd8647dd5e488089b990661a66e96c2022-12-22T00:14:35ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602020-02-0192111510.18637/jss.v092.i021332The Calculus of M-Estimation in R with geexBradley C. SaulMichael G. HudgensM-estimation, or estimating equation, methods are widely applicable for point estimation and asymptotic inference. In this paper, we present an R package that can find roots and compute the empirical sandwich variance estimator for any set of user-specified, unbiased estimating equations. Examples from the M-estimation primer by Stefanski and Boos (2002) demonstrate use of the software. The package also includes a framework for finite sample, heteroscedastic, and autocorrelation variance corrections, and a website with an extensive collection of tutorials.https://www.jstatsoft.org/index.php/jss/article/view/3470empirical sandwich variance estimatorestimating equationsm-estimationrobust statisticsr |
| spellingShingle | Bradley C. Saul Michael G. Hudgens The Calculus of M-Estimation in R with geex Journal of Statistical Software empirical sandwich variance estimator estimating equations m-estimation robust statistics r |
| title | The Calculus of M-Estimation in R with geex |
| title_full | The Calculus of M-Estimation in R with geex |
| title_fullStr | The Calculus of M-Estimation in R with geex |
| title_full_unstemmed | The Calculus of M-Estimation in R with geex |
| title_short | The Calculus of M-Estimation in R with geex |
| title_sort | calculus of m estimation in r with geex |
| topic | empirical sandwich variance estimator estimating equations m-estimation robust statistics r |
| url | https://www.jstatsoft.org/index.php/jss/article/view/3470 |
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