Consistency and asymptotic normality of Maximum Likelihood estimators of Autoregressive Random Coefficient Models
| dc.contributor.author | Yacef, Cylia | |
| dc.date.accessioned | 2024-10-29T11:01:53Z | |
| dc.date.available | 2024-10-29T11:01:53Z | |
| dc.date.issued | 2020 | |
| dc.description | 89f.,ill.;30cm | |
| dc.description.abstract | his dissertation is devoted to the study of some properties of the random coefficient au- toregressive process. This process is commonly referred to as a sequence 89ffully described by its past values multiplied by random coefficients and disturbed by white noise. We treat some problems of the study of such processes: stationarity, conditions of existence of a stationary solution and unknown parameters estimation. We end this work with sim- ulations carried out by the R languag | |
| dc.identifier.citation | probabilités et statistiques | |
| dc.identifier.uri | https://dspace.ummto.dz/handle/ummto/25004 | |
| dc.language.iso | en | |
| dc.publisher | ummto | |
| dc.subject | Estimation | |
| dc.subject | Autoregressive models | |
| dc.subject | Random Coefficients autoregressive | |
| dc.subject | Maximum likelihood estimation | |
| dc.title | Consistency and asymptotic normality of Maximum Likelihood estimators of Autoregressive Random Coefficient Models | |
| dc.type | Thesis |