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CONSISTENT AND ASYMPTOTICALLY NORMAL ESTIMATORS FOR PERIODIC BILINEAR MODELS
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 Title & Authors
CONSISTENT AND ASYMPTOTICALLY NORMAL ESTIMATORS FOR PERIODIC BILINEAR MODELS
Bibi, Abdelouahab; Gautier, Antony;
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 Abstract
In this paper, a distribution free approach to the parameter estimation of a simple bilinear model with periodic coefficients is presented. The proposed method relies on minimum distance estimator based on the autocovariances of the squared process. Consistency and asymptotic normality of the estimator, as well as hypotheses testing, are derived. Numerical experiments on simulated data sets are presented to highlight the theoretical results.
 Keywords
bilinear time series;periodic coefficients;minimum distance estimator;asymptotic normality;hypotheses testing;
 Language
English
 Cited by
1.
On periodic time-varying bilinear processes: structure and asymptotic inference, Statistical Methods & Applications, 2016, 25, 3, 395  crossref(new windwow)
2.
Minimum distance estimation of Markov-switching bilinear processes, Statistics, 2016, 50, 6, 1290  crossref(new windwow)
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