Coherent Forecasting in Binomial AR(p) Model

Title & Authors
Coherent Forecasting in Binomial AR(p) Model
Kim, Hee-Young; Park, You-Sung;

Abstract
This article concerns the forecasting in binomial AR(p) models which is proposed by Wei$\small{\ss}$ (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$\small{\ss}$ (2009b).
Keywords
Binomial thinning;binomial AR(p) model;block-of-blocks bootstrap;
Language
English
Cited by
1.
Markov Chain Approach to Forecast in the Binomial Autoregressive Models,;;

Communications for Statistical Applications and Methods, 2010. vol.17. 3, pp.441-450
1.
Binomial AR(1) processes: moments, cumulants, and estimation, Statistics, 2013, 47, 3, 494
2.
Parameter estimation for binomial AR(1) models with applications in finance and industry, Statistical Papers, 2013, 54, 3, 563
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