An INAR(1) negative multinomial regression model for longitudinal count data

DOI10.1007/BF02294319zbMath1365.62450MaRDI QIDQ2250659

Ulf Böckenholt

Publication date: 18 July 2014

Published in: Psychometrika (Search for Journal in Brave)

zbMATH Keywords

Poisson distributionMarkov modelsbinomial thinning

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to psychology (62P15)

Related Items (7)

Efficient Estimation of Auto-Regression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models ⋮ A general family of limited information goodness-of-fit statistics for multinomial data ⋮ The asymptotic structure of nearly unstable non-negative integer-valued AR(1) models ⋮ Correlated risks vs contagion in stochastic transition models ⋮ A multinomial autoregressive model for finite-range time series of counts ⋮ Generalized RCINAR(p) Process with Signed Thinning Operator ⋮ Inference for Random Coefficient INAR(1) Process Based on Frequency Domain Analysis

Uses Software

• GAUSS

Cites Work

• Longitudinal data analysis using generalized linear models
• Discrete analogues of self-decomposability and stability
• Some Covariance Models for Longitudinal Count Data with Overdispersion
• Markov Regression Models for Time Series: A Quasi-Likelihood Approach
• Mixed Poisson Likelihood Regression Models for Longitudinal Interval Count Data
• Negative binomial and mixed poisson regression
• Some ARMA models for dependent sequences of poisson counts
• FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
• A Class of Distributions Applicable to Accidents
• On the Distribution of the Likelihood Ratio
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