Conditional maximum likelihood estimation for a class of observation-driven time series models for count data

DOI10.1016/j.spl.2016.11.002zbMath1417.62241OpenAlexW2566497099MaRDI QIDQ511583

Qi Zheng, Yunwei Cui

Publication date: 21 February 2017

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2016.11.002

zbMATH Keywords

time series of countsobservation-driven modelsINGARCH\((p,q)\) modelsone-parameter exponential family

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09)

Related Items (8)

Minimum density power divergence estimator for negative binomial integer-valued GARCH models ⋮ Test of parameter changes in a class of observation-driven models for count time series ⋮ Consistent model selection procedure for general integer-valued time series ⋮ A marginal moment matching approach for fitting endemic‐epidemic models to underreported disease surveillance counts ⋮ Testing for the Poisson-Tweedie distribution ⋮ Robust estimation for general integer-valued time series models ⋮ Mean targeting estimator for the integer-valued GARCH(1, 1) model ⋮ Conditional maximum likelihood estimation in negative binomial INGARCH processes with known number of successes when the true parameter is at the boundary of the parameter space

Cites Work

• Correction to ``On weak dependence conditions for Poisson autoregressions
• On weak dependence conditions for Poisson autoregressions
• Inference and testing for structural change in general Poisson autoregressive models
• Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach
• Weakly dependent chains with infinite memory
• GARCH processes: structure and estimation
• A new weak dependence condition and applications to moment inequalities
• Poisson QMLE of Count Time Series Models
• Theory and inference for a class of nonlinear models with application to time series of counts
• QUASI-LIKELIHOOD INFERENCE FOR NEGATIVE BINOMIAL TIME SERIES MODELS
• Poisson Autoregression
• A negative binomial model for time series of counts
• Integer-Valued GARCH Process
• A negative binomial integer-valued GARCH model

This page was built for publication: Conditional maximum likelihood estimation for a class of observation-driven time series models for count data