Abstract
The uniform asymptotic normality of the fixed accuracy estimate for the parameter in explosive autoregressive process of the first order is established. The asymptotic optimality of the estimate in minimax sense for sufficiently broad class of loss functions is shown. The fixed-accuracy estimate is constructed as a sequential modification of the least squares estimate.
| Original language | English |
|---|---|
| Pages (from-to) | 25-78 |
| Number of pages | 54 |
| Journal | Sequential Analysis |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 1993 |
Keywords
- asymptotic normality
- autoregressive process
- optimality in minimax sense
- sequential estimate
- stopping time
ASJC Scopus subject areas
- Modelling and Simulation
- Statistics and Probability
Fingerprint Dive into the research topics of 'On optimality of the fixed-accuracy estimate of the parameter in an explosive autoregressive process of the first order'. Together they form a unique fingerprint.
Cite this
Konev, V. V., & Pergamenshchikov, S. M. (1993). On optimality of the fixed-accuracy estimate of the parameter in an explosive autoregressive process of the first order. Sequential Analysis, 12(1), 25-78. https://doi.org/10.1080/07474949308836269