Bootstrap prediction intervals in state-space models
نویسندگان
چکیده
منابع مشابه
Bootstrap Prediction Intervals in State Space Models
Prediction intervals in State Space models can be obtained by assuming Gaussian innovations and using the prediction equations of the Kalman filter, where the true parameters are substituted by consistent estimates. This approach has two limitations. First, it does not incorporate the uncertainty due to parameter estimation. Second, the Gaussianity assumption of future innovations may be inaccu...
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One of the main goals of studying the time series is estimation of prediction interval based on an observed sample path of the process. In recent years, different semiparametric bootstrap methods have been proposed to find the prediction intervals without any assumption of error distribution. In semiparametric bootstrap methods, a linear process is approximated by an autoregressive process. The...
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ژورنال
عنوان ژورنال: Journal of Time Series Analysis
سال: 2009
ISSN: 0143-9782,1467-9892
DOI: 10.1111/j.1467-9892.2008.00604.x