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- W2073607838 abstract "The variability of parameter estimates is commonly neglected when constructing prediction intervals based on a parametric model for a time series. This practice is due to the complexity of conditioning the inference on information such as observed values of the underlying stochastic process. In this paper, conditional prediction intervals when using autoregression forecasts are proposed whose simple implementation will hopefully enable wide use. A simulation study illustrates the improvement over classical intervals in terms of empirical coverage." @default.
- W2073607838 created "2016-06-24" @default.
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- W2073607838 date "2000-03-01" @default.
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- W2073607838 title "Prediction Intervals Based on Autoregression Forecasts" @default.
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- W2073607838 doi "https://doi.org/10.1111/1467-9884.00222" @default.
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