Inferential methods for an unconstrained nonstationary BINMA time series process with Poisson innovations

DOI10.1080/15598608.2016.1258600zbMath1435.62331OpenAlexW2551222229MaRDI QIDQ2323262

Yanyan Li

Publication date: 30 August 2019

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15598608.2016.1258600

zbMATH Keywords

time seriesquasi-likelihoodmoving averagebivariate

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (7)

Communication in Statistics-Theory and methods improved GQL estimation method for the generalised BINMA(1) model ⋮ BINMA(1) model with COM-Poisson innovations: Estimation and application ⋮ A GQL estimation approach for analysing non-stationary over-dispersed BINAR(1) time series ⋮ Modelling with dispersed bivariate moving average processes ⋮ A BINAR(1) time-series model with cross-correlated COM–Poisson innovations ⋮ A GQL-based inference in non-stationary BINMA(1) time series ⋮ Inference for bivariate integer-valued moving average models based on binomial thinning operation

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