sphet: Spatial Models with Heteroskedastic Innovations in R
<b>sphet</b> is a package for estimating and testing spatial models with heteroskedastic innovations. We implement recent generalized moments estimators and semiparametric methods for the estimation of the coefficients variance-covariance matrix. This paper is a general description of &l...
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2010-10-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | http://www.jstatsoft.org/v35/i01/paper |
| _version_ | 1811204781030506496 |
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| author | Gianfranco Piras |
| author_facet | Gianfranco Piras |
| author_sort | Gianfranco Piras |
| collection | DOAJ |
| description | <b>sphet</b> is a package for estimating and testing spatial models with heteroskedastic innovations. We implement recent generalized moments estimators and semiparametric methods for the estimation of the coefficients variance-covariance matrix. This paper is a general description of <b>sphet</b> and all functionalities are illustrated by application to the popular Boston housing dataset. The package in its current version is limited to the estimators based on Arraiz, Drukker, Kelejian, and Prucha (2010); Kelejian and Prucha (2007, 2010). The estimation functions implemented in <b>sphet</b> are able to deal with virtually any sample size. |
| first_indexed | 2024-04-12T03:18:23Z |
| format | Article |
| id | doaj.art-34f99e0edf6147a28ee9f133b7b81c32 |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-04-12T03:18:23Z |
| publishDate | 2010-10-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-34f99e0edf6147a28ee9f133b7b81c322022-12-22T03:49:58ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602010-10-013501sphet: Spatial Models with Heteroskedastic Innovations in RGianfranco Piras<b>sphet</b> is a package for estimating and testing spatial models with heteroskedastic innovations. We implement recent generalized moments estimators and semiparametric methods for the estimation of the coefficients variance-covariance matrix. This paper is a general description of <b>sphet</b> and all functionalities are illustrated by application to the popular Boston housing dataset. The package in its current version is limited to the estimators based on Arraiz, Drukker, Kelejian, and Prucha (2010); Kelejian and Prucha (2007, 2010). The estimation functions implemented in <b>sphet</b> are able to deal with virtually any sample size.http://www.jstatsoft.org/v35/i01/paperspatial modelsRcomputational methodssemiparametric methodskernel functionsheteroskedasticity |
| spellingShingle | Gianfranco Piras sphet: Spatial Models with Heteroskedastic Innovations in R Journal of Statistical Software spatial models R computational methods semiparametric methods kernel functions heteroskedasticity |
| title | sphet: Spatial Models with Heteroskedastic Innovations in R |
| title_full | sphet: Spatial Models with Heteroskedastic Innovations in R |
| title_fullStr | sphet: Spatial Models with Heteroskedastic Innovations in R |
| title_full_unstemmed | sphet: Spatial Models with Heteroskedastic Innovations in R |
| title_short | sphet: Spatial Models with Heteroskedastic Innovations in R |
| title_sort | sphet spatial models with heteroskedastic innovations in r |
| topic | spatial models R computational methods semiparametric methods kernel functions heteroskedasticity |
| url | http://www.jstatsoft.org/v35/i01/paper |
| work_keys_str_mv | AT gianfrancopiras sphetspatialmodelswithheteroskedasticinnovationsinr |