Keyword: ARMA process, censoring, spectral likelihood, MCMC, simulation

論文タイトル A spectral estimator of ARMA parameters from thresholded data
出版情報 Statistics and Computing, Volume 12, Number 4 (2002)
著者 David J. Allcroft and Chris A. Glasbey
概要(abstract) "We consider computationally-fast methods for estimating parameters in ARMA processes from binary time series data, obtained by thresholding the latent ARMA process. All methods involve matching estimated and expected autocorrelations of the binary series. In particular, we focus on the spectral representation of the likelihood of an ARMA process and derive a restricted form of this likelihood, which uses correlations at only the first few lags. We contrast these methods with an efficient but computationally-intensive Markov chain Monte Carlo (MCMC) method. In a simulation study we show that, for a range of ARMA processes, the spectral method is more efficient than variants of least squares and much faster than MCMC. We illustrate by fitting an ARMA(2,1) model to a binary time series of cow feeding data."
使用されているNAG製品 パラメータの推定にNAG Fotran Library の最適化ルーチン E04JAF が使用されている。


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