Coherent Forecasting in Binomial AR(p) Model
Coherent Forecasting in Binomial AR(p) Model
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DOI：
10.5351/ckss.2010.17.1.027
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发表时间：
2010-01
影响因子：
0.4
通讯作者：
H. Kim;Yousung Park
中科院分区：
文献类型：
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作者：
H. Kim;Yousung Park
本文研究了Wei（2009 b）提出的二项AR（p）模型对二项计数时间序列的预测。我们的方法扩展到二项式AR（p）模型，最近的结果由Jung和Tremayne（2006）为二阶整数值自回归模型，INAR（2），简单的泊松创新。预测是由条件中位数，它给出了“连贯”的预测，我们估计的二项式AR（p）模型的未来值的预测分布的Monte Carlo方法允许参数的不确定性。模型参数估计的矩的方法和估计的标准误差计算的块的块自助法。该方法适用于Wei（2009 b）的测井数据集。
This article concerns the forecasting in binomial AR(p) models which is proposed by Wei (2009b) for time series of binomial counts. Our method extends to binomial AR(p) models a recent result by Jung and Tremayne (2006) for integer-valued autoregressive model of second order, INAR(2), with simple Poisson innovations. Forecasts are produced by conditional median which gives 'coherent' forecasts, and we estimate the forecast distributions of future values of binomial AR(p) models by means of a Monte Carlo method allowing for parameter uncertainty. Model parameters are estimated by the method of moments and estimated standard errors are calculated by means of block of block bootstrap. The method is fitted to log data set used in Wei (2009b).