Generalized Additive Models for Location Scale and Shape (GAMLSS) in R
GAMLSS is a general framework for fitting regression type models where the distribution of the response variable does not have to belong to the exponential family and includes highly skew and kurtotic continuous and discrete distribution. GAMLSS allows all the parameters of the distribution of the r...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2007-11-01
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| Series: | Journal of Statistical Software |
| Subjects: | |
| Online Access: | http://www.jstatsoft.org/v23/i07/paper |
| _version_ | 1818986230847635456 |
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| author | D. Mikis Stasinopoulos Robert A. Rigby |
| author_facet | D. Mikis Stasinopoulos Robert A. Rigby |
| author_sort | D. Mikis Stasinopoulos |
| collection | DOAJ |
| description | GAMLSS is a general framework for fitting regression type models where the distribution of the response variable does not have to belong to the exponential family and includes highly skew and kurtotic continuous and discrete distribution. GAMLSS allows all the parameters of the distribution of the response variable to be modelled as linear/non-linear or smooth functions of the explanatory variables. This paper starts by defining the statistical framework of GAMLSS, then describes the current implementation of GAMLSS in R and finally gives four different data examples to demonstrate how GAMLSS can be used for statistical modelling. |
| first_indexed | 2024-12-20T18:47:30Z |
| format | Article |
| id | doaj.art-9db1d2b123eb42bdb86065fedd9ee90d |
| institution | Directory Open Access Journal |
| issn | 1548-7660 |
| language | English |
| last_indexed | 2024-12-20T18:47:30Z |
| publishDate | 2007-11-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj.art-9db1d2b123eb42bdb86065fedd9ee90d2022-12-21T19:29:40ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602007-11-01237Generalized Additive Models for Location Scale and Shape (GAMLSS) in RD. Mikis StasinopoulosRobert A. RigbyGAMLSS is a general framework for fitting regression type models where the distribution of the response variable does not have to belong to the exponential family and includes highly skew and kurtotic continuous and discrete distribution. GAMLSS allows all the parameters of the distribution of the response variable to be modelled as linear/non-linear or smooth functions of the explanatory variables. This paper starts by defining the statistical framework of GAMLSS, then describes the current implementation of GAMLSS in R and finally gives four different data examples to demonstrate how GAMLSS can be used for statistical modelling.http://www.jstatsoft.org/v23/i07/paperBox-Cox transformationcentile estimationcubic smoothing splinesLMS methodnegative binomialnon-normalnon-parametricoverdispersionpenalized likelihoodskewness and kurtosis |
| spellingShingle | D. Mikis Stasinopoulos Robert A. Rigby Generalized Additive Models for Location Scale and Shape (GAMLSS) in R Journal of Statistical Software Box-Cox transformation centile estimation cubic smoothing splines LMS method negative binomial non-normal non-parametric overdispersion penalized likelihood skewness and kurtosis |
| title | Generalized Additive Models for Location Scale and Shape (GAMLSS) in R |
| title_full | Generalized Additive Models for Location Scale and Shape (GAMLSS) in R |
| title_fullStr | Generalized Additive Models for Location Scale and Shape (GAMLSS) in R |
| title_full_unstemmed | Generalized Additive Models for Location Scale and Shape (GAMLSS) in R |
| title_short | Generalized Additive Models for Location Scale and Shape (GAMLSS) in R |
| title_sort | generalized additive models for location scale and shape gamlss in r |
| topic | Box-Cox transformation centile estimation cubic smoothing splines LMS method negative binomial non-normal non-parametric overdispersion penalized likelihood skewness and kurtosis |
| url | http://www.jstatsoft.org/v23/i07/paper |
| work_keys_str_mv | AT dmikisstasinopoulos generalizedadditivemodelsforlocationscaleandshapegamlssinr AT robertarigby generalizedadditivemodelsforlocationscaleandshapegamlssinr |