Your browser doesn't support javascript.
loading
Heteroscedastic partially linear model under skew-normal distribution with application in ragweed pollen concentration.
Ferreira, Clécio S; Borelli Zeller, Camila; de Oliveira Garcia, Rafael R.
Afiliação
  • Ferreira CS; Departamento de Estatística, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil.
  • Borelli Zeller C; Departamento de Estatística, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil.
  • de Oliveira Garcia RR; Departamento de Estatística, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil.
J Appl Stat ; 50(6): 1255-1282, 2023.
Article em En | MEDLINE | ID: mdl-37025282
We introduce a new class of heteroscedastic partially linear model (PLM) with skew-normal distribution. Maximum likelihood estimation of the model parameters by the ECM algorithm (Expectation/Conditional Maximization) as well as influence diagnostics for the new model are investigated. In addition, a Likelihood Ratio test for assessing the homogeneity of the scale parameter is presented. Simulation studies for assessing the performance of the ECM algorithm and the Likelihood Ratio test statistics for homogeneity of variance are developed. Also, a study for misspecification of the structure function is considered. Finally, an application of the new heteroscedastic PLM to a real data set on ragweed pollen concentration is presented to show that it provides a better fit than the classic homocedastic PLM. We hope that the proposed model may attract applications in different areas of knowledge.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Appl Stat Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Appl Stat Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido