Abstract
For a first-order non-explosive autoregressive process with dependent noise, we propose a truncated sequential procedure with a fixed mean-square accuracy. The asymptotic distribution of the estimator depends on the type of the noise distribution: it is normal when the noise has a Kotz's distribution, while it is a mixture of normal distributions if the noise distribution is a variance mixture of normal distrbutions as well. In both cases, the convergence to the limiting distribution is uniform in the unknown parameter.
| Original language | English |
|---|---|
| Pages (from-to) | 43-58 |
| Number of pages | 16 |
| Journal | Mathematical Methods of Statistics |
| Volume | 18 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Mar 2009 |
Keywords
- autoregression model
- truncated sequential estimators
- uniform normality
ASJC Scopus subject areas
- Statistics, Probability and Uncertainty
- Statistics and Probability
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Fourdrinier, D., Konev, V., & Pergamenshchikov, S. (2009). Truncated sequential estimation of the parameter of a first order autoregressive process with dependent noises. Mathematical Methods of Statistics, 18(1), 43-58. https://doi.org/10.3103/S1066530709010037