Bayesian analysis of some outlier problems in time series
暂无分享,去创建一个
SUMMARY Two models, the aberrant innovation model and the aberrant observation model, are considered to characterize outliers in time series. The approach adopted here allows for a small probability a that any given observation is 'bad' and in this set-up the inference about the parameters of an autoregressive model is considered.
[1] W. J. Dixon,et al. Processing Data for Outliers , 1953 .
[2] J. Tukey. A survey of sampling from contaminated distributions , 1960 .
[3] G. C. Tiao,et al. A bayesian approach to some outlier problems. , 1968, Biometrika.
[4] M. Otto,et al. Outliers in Time Series , 1972 .
[5] G. C. Tiao,et al. Bayesian inference in statistical analysis , 1973 .
[6] Bovas Abraham,et al. Linear Models and Spurious Observations , 1978 .