Electronic Resource
Springer
Annals of the Institute of Statistical Mathematics
40 (1988), S. 507-520
ISSN:
1572-9052
Keywords:
Autoregressive process
;
local asymptotic normality
;
Monte Carlo
;
parameter estimation
;
stochastic search
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract We consider a local random searching method to approximate a root of a specified equation. If such roots, which can be regarded as estimators for the Euclidean parameter of a statistical experiment, have some asymptotic optimality properties, the local random searching method leads to asymptotically optimal estimators in such cases. Application to simple first order autoregressive processes and some simulation results for such models are also included.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00053062
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