Forecasting evaluation via parametric bootstrap for threshold-INARCH models
  • Kim, Deok Ryun
  • Hwang, Sun Young
Citations

WEB OF SCIENCE

5
Citations

SCOPUS

3

초록

This article is concerned with the issue of forecasting and evaluation of threshold-asymmetric volatility models for time series of count data. In particular, threshold integer-valued models with conditional Poisson and conditional negative binomial distributions are highlighted. Based on the parametric bootstrap method, some evaluation measures are discussed in terms of one-step ahead forecasting. A parametric bootstrap procedure is explained from which directional measure, magnitude measure and expected cost of misclassification are discussed to evaluate competing models. The cholera data in Bangladesh from 1988 to 2016 is analyzed as a real application.

제목
Forecasting evaluation via parametric bootstrap for threshold-INARCH models
저자
Kim, Deok RyunHwang, Sun Young
DOI
10.29220/CSAM.2020.27.2.177
발행일
2020-03
유형
Article
저널명
Communications for Statistical Applications and Methods
27
2
페이지
177 ~ 187