Modelling of count data using nonparametric mixtures
| Autor: | Chew-Seng Chee |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Statistics and Probability
Statistics::Theory Economics and Econometrics Nonparametric skew Poisson distribution 01 natural sciences Least squares 010104 statistics & probability symbols.namesake 0502 economics and business Statistics Statistics::Methodology Mixture distribution 0101 mathematics 050205 econometrics Parametric statistics Mathematics Applied Mathematics 05 social sciences Nonparametric statistics Nonparametric regression Modeling and Simulation symbols Social Sciences (miscellaneous) Analysis Count data |
| Zdroj: | AStA Advances in Statistical Analysis. 100:239-257 |
| ISSN: | 1863-818X 1863-8171 |
| DOI: | 10.1007/s10182-015-0255-7 |
| Popis: | Nonparametric modelling of count data is partly motivated by the fact that using parametric count models not only runs the risk of model misspecification but also is rather restrictive in terms of local approximation. Accordingly, we present a framework of using nonparametric mixtures for flexible modelling of count data. We consider the use of the least squares function in nonparametric mixture modelling and provide two algorithms for least squares fitting of nonparametric mixtures. Two illustrations of the framework are given, each with a particular nonparametric mixture. One illustration is the use of the nonparametric Poisson mixture for general modelling purposes. The other illustration is concerned with modelling of count data from some decreasing distribution, in which the Poisson mixture distribution is less appropriate, for its fitted distribution might not be a decreasing distribution. We define a mixture distribution called the discrete decreasing beta mixture distribution that always has fitted probabilities conforming with the assumption of decreasing probabilities. Through numerical studies, we demonstrate the performance of nonparametric mixtures as modelling tools. |
| Databáze: | OpenAIRE |
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