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|a 10.1080/02664763.2021.2024798
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|a eng
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|a Ferreira, Clécio S
|e verfasserin
|4 aut
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|a Heteroscedastic partially linear model under skew-normal distribution with application in ragweed pollen concentration
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|c 2023
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Revised 16.09.2024
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|a published: Electronic-eCollection
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|a Citation Status PubMed-not-MEDLINE
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|a © 2022 Informa UK Limited, trading as Taylor & Francis Group.
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|a 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
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|a Journal Article
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|a ECM algorithm
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|a Partially linear models
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|a heteroscedasticity
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|a local influence
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| 650 |
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|a skew-normal distribution
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1 |
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|a Borelli Zeller, Camila
|e verfasserin
|4 aut
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| 700 |
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|a de Oliveira Garcia, Rafael R
|e verfasserin
|4 aut
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|i Enthalten in
|t Journal of applied statistics
|d 1991
|g 50(2023), 6 vom: 30., Seite 1255-1282
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|x 0266-4763
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|g volume:50
|g year:2023
|g number:6
|g day:30
|g pages:1255-1282
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|u http://dx.doi.org/10.1080/02664763.2021.2024798
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