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Bootstrap Confidence Intervals for the INAR(p) Process
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 Title & Authors
Bootstrap Confidence Intervals for the INAR(p) Process
Kim, Hee-Young; Park, You-Sung;
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 Abstract
The distributional properties of forecasts in an integer-valued time series model have not been discovered yet mainly because of the complexity arising from the binomial thinning operator. We propose two bootstrap methods to obtain nonparametric prediction intervals for an integer-valued autoregressive model : one accommodates the variation of estimating parameters and the other does not. Contrary to the results of the continuous ARMA model, we show that the latter is better than the former in forecasting the future values of the integer-valued autoregressive model.
 Keywords
Stationary process;Integer valued time series;Prediction interval;Sieve Bootstrap;
 Language
Korean
 Cited by
1.
Coherent Forecasting in Binomial AR(p) Model,;;

Communications for Statistical Applications and Methods, 2010. vol.17. 1, pp.27-37 crossref(new window)
2.
Markov Chain Approach to Forecast in the Binomial Autoregressive Models,;;

Communications for Statistical Applications and Methods, 2010. vol.17. 3, pp.441-450 crossref(new window)
1.
Coherent Forecasting in Binomial AR(p) Model, Communications for Statistical Applications and Methods, 2010, 17, 1, 27  crossref(new windwow)
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