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                                       Details for article 12 of 20 found articles
 
 
  Maximum likelihood estimation using differences in an autoregressive-1 process
 
 
Title: Maximum likelihood estimation using differences in an autoregressive-1 process
Author: Wilson, P. David
Appeared in: Communications in statistics
Paging: Volume 17 (1988) nr. 1 pages 17-26
Year: 1988
Contents: In a first-order autoregressive (AR-1) process with unknown mean, conventional maximum likelihood analysis requires joint estimation of the mean and AR coefficient. Differencing the series removes the mean, and for short series it should be more efficient to estimate the AR coefficient from the likelihood function of the differences. The exact likelihood function of the differences is given. A computer simulation study compares the behavior of the estimator obtained by maximizing the likelihood of the differences with that of the conventional maximum likelihood estimator. A root-mean-squared-error criterion shows superiority of the estimator based on differences for series of 50 time points or less.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 12 of 20 found articles
 
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