A semi-parametric additive model for variance heterogeneity
| Autor: | Robert A. Rigby, D. M. Stasinopoulos |
|---|---|
| Rok vydání: | 1996 |
| Předmět: |
Statistics and Probability
Smoothness (probability theory) Variance (accounting) Interaction Theoretical Computer Science Semiparametric model One-way analysis of variance Computational Theory and Mathematics Statistics Statistics Probability and Uncertainty Variance-based sensitivity analysis Additive model Variance function Mathematics |
| Zdroj: | Statistics and Computing. 6:57-65 |
| ISSN: | 1573-1375 0960-3174 |
| DOI: | 10.1007/bf00161574 |
| Popis: | This paper presents a flexible model for variance heterogeneity in a normal error model. Specifically, both the mean and variance are modelled using semi-parametric additive models. We call this model a ‘Mean And Dispersion Additive Model’ (MADAM). A successive relaxation algorithm for fitting the model is described and justified as maximizing a penalized likelihood function with penalties for lack of smoothness in the additive non-parametric functions in both mean and variance models. The algorithm is implemented in GLIM4, allowing flexible and interactive modelling of variance heterogeneity. Two data sets are used for demonstration. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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