Recursive Method for AR Parameter in the Presence of Outlier in Poisson Noise
نویسندگان
چکیده
Submitted: Apr 23, 2013; Accepted: Jun 2, 2013; Published: Jun 20, 2013 Abstract: The study of outliers is an essential part in the field of time series as the presence of one or more outliers can seriously damage the estimation in model. Outliers in time discrete Systems, have been studied [1] and a test statistic for the detection of extreme observations has been developed [2]. If through the suggested test-statistic, it is decided that an outlier has occurred in the autoregressive model with Poisson distribution, then the particular observation y can be discarded and replaced by a forecast of the true value, as a remedial t measure and the forecast is made on previous known observations. A minimum variance estimate in the sense of least square has been established in this study through Kalman Filtering recursive method.
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