Improved estimation for Poisson INAR(1) models

DOI10.1080/00949655.2014.930862zbMath1457.62256OpenAlexW2085239753MaRDI QIDQ5220877

Klaus L. P. Vasconcellos, Marcelo Bourguignon

Publication date: 27 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2014.930862

zbMATH Keywords

bias correctionconditional maximum likelihood estimatorPoisson INAR(1) processconditional least-squares estimatorsquared difference estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10)

Related Items (12)

The effects of additive outliers in INAR(1) process and robust estimation ⋮ Bias corrections for moment estimators in Poisson INAR(1) and INARCH(1) processes ⋮ Computing with bivariate COM-Poisson model under different copulas ⋮ A new estimation for INAR(1) process with Poisson distribution ⋮ Modelling with the novel INAR(1)-PTE process ⋮ On residual CUSUM statistic for PINAR(1) model in statistical design and diagnostic of control chart ⋮ A flexible observation-driven stationary bivariate negative binomial INAR(1) with non-homogeneous levels of over-dispersion ⋮ Bias-correction of some estimators in the INAR(1) process ⋮ A GQL estimation approach for analysing non-stationary over-dispersed BINAR(1) time series ⋮ Higher autocumulant functions for ADCINAR(1) process and bias-correction of some estimators ⋮ A BINAR(1) time-series model with cross-correlated COM–Poisson innovations ⋮ Modeling longitudinal INMA(1) with COM-Poisson innovation under non-stationarity: application to medical data

Cites Work

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• Simultaneous confidence regions for the parameters of a Poisson \(INAR(1)\) model
• Some asymptotic properties in INAR(1) processes with Poisson marginals
• Unit root testing in integer-valued AR(1) models
• Asymptotic properties of CLS estimators in the Poisson AR(1) model
• Modelling Count Data Time Series with Markov Processes Based on Binomial Thinning
• Difference Equations for the Higher‐Order Moments and Cumulants of the INAR(1) Model
• Analysis of low count time series data by poisson autoregression
• FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
• Process capability analysis for serially dependent processes of Poisson counts
• First Order Autoregression: Inference, Estimation, and Prediction
• NOTE ON BIAS IN THE ESTIMATION OF AUTOCORRELATION

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