Modelling and coherent forecasting of zero-inflated count time series

DOI10.1177/1471082X13520425OpenAlexW2330681386MaRDI QIDQ4970997

Apratim Guha, Atanu Biswas, Raju Maiti, Seng Huat Ong

Publication date: 8 October 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x13520425

zbMATH Keywords

zero-inflated Poissoncoherent forecastingPegram's operator

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

Zero-Inflated NGINAR(1) process ⋮ Testing for zero inflation and overdispersion in INAR(1) models ⋮ Inferential aspects of the zero-inflated Poisson INAR(1) process ⋮ Auto-association measures for stationary time series of categorical data ⋮ Integer-valued autoregressive processes with prespecified marginal and innovation distributions: a novel perspective

Cites Work

• Unnamed Item
• Unnamed Item
• Discrete-valued ARMA processes
• A Bayesian analysis of zero-inflated generalized Poisson model
• A new geometric first-order integer-valued autoregressive (NGINAR(1)) process
• Time series: theory and methods
• Discrete analogues of self-decomposability and stability
• Maximum-likelihood estimation for hidden Markov models
• On conditional least squares estimation for stochastic processes
• Coherent forecasting for stationary time series of discrete data
• Regression theory for categorical time series
• Statistical analysis of discrete-valued time series using categorical ARMA models
• Time series analysis of categorical data using auto-mutual information
• Self-exciting hurdle models for terrorist activity
• Consistency of the maximum likelihood estimator for general hidden Markov models
• An integer-valued pth-order autoregressive structure (INAR(p)) process
• Autoregressive moving-average processes with negative-binomial and geometric marginal distributions
• Some ARMA models for dependent sequences of poisson counts
• An autoregressive model for multilag Markov chains
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• Markov zero-inflated Poisson regression models for a time series of counts with excess zeros
• FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
• Regression analysis of zero-inflated time-series counts: application to air pollution related emergency room visit data

This page was built for publication: Modelling and coherent forecasting of zero-inflated count time series