Modeling time series of counts with a new class of INAR(1) model

DOI10.1007/S00362-015-0704-0zbMath1367.60033OpenAlexW2159735653MaRDI QIDQ2359164

Wooi Chen Khoo, Atanu Biswas, Seng Huat Ong

Publication date: 27 June 2017

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

Full work available at URL: https://doi.org/10.1007/s00362-015-0704-0

zbMATH Keywords

robustnessEM algorithmstationarityadditive outliersINAR(1) modelthinning operatorinnovative outliersPegram operator

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Stationary stochastic processes (60G10)

Related Items (10)

An EM algorithm for estimation of the parameters of the geometric minification INAR model ⋮ An INAR(1) model based on the Pegram and thinning operators with serially dependent innovation ⋮ Zero-and-one inflated Poisson–Lindley INAR(1) process for modelling count time series with extra zeros and ones ⋮ Poisson autoregressive process modeling via the penalized conditional maximum likelihood procedure ⋮ A seasonal geometric INAR process based on negative binomial thinning operator ⋮ Model-based INAR bootstrap for forecasting INAR\((p)\) models ⋮ A new class of INAR(1) model for count time series ⋮ Mean targeting estimator for the integer-valued GARCH(1, 1) model ⋮ A new INAR(1) process with bounded support for counts showing equidispersion, underdispersion and overdispersion ⋮ An integer-valued bilinear time series model via two random operators

Uses Software

• itsmr

Cites Work

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