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On the statistical inference of a machine‐generated autoregressive AR(1) model
Author(s) -
Stockis J.P,
Tong H.
Publication year - 1998
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00154
Subject(s) - autoregressive model , estimator , asymptotic distribution , robustness (evolution) , statistical inference , independence (probability theory) , limiting , mathematics , inference , statistics , econometrics , computer science , algorithm , artificial intelligence , engineering , mechanical engineering , biochemistry , chemistry , gene
We have obtained the asymptotic bias and the limiting distribution for the Yule–Walker estimator of the autoregressive parameter under a considerably weaker assumption than that of independence in the noise sequence. Among other things, these suggest robustness of the classical results and throw some light on the use of simulations based on pseudorandom numbers in verifying these results.