A study on the integer-valued time series models with overdispersion
碩士 === 國立中山大學 === 應用數學系研究所 === 101 === Time series of counts observed in practice often exhibit overdispersion. The integer-valued generalized autoregressive conditional heteroscedastic (Ingarch) models are commonly used for count time series with overdispersion. We assume the conditional mean of an...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2013
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/05765042285169986771 |
| Summary: | 碩士 === 國立中山大學 === 應用數學系研究所 === 101 === Time series of counts observed in practice often exhibit overdispersion. The integer-valued generalized autoregressive conditional heteroscedastic (Ingarch) models are commonly used for count time series with overdispersion. We assume the conditional mean of an Ingarch model follows a Poisson distribution or other distributions, such as the negative Binomial distribution or the Generalized Poisson distribution. In this study, we investigate the properties, estimation of these Ingarch models. Two estimation methods: conditional least squares and maximum likelihood approach are considered. Numerical studies are performed to compare the properties and estimation of these Ingarch models.
|
|---|