Consistency and asymptotic normality of least squares estimators in generalized STAR models

DOI10.1111/j.1467-9574.2008.00391.xMaRDI QIDQ6573188

Budi Nurani Ruchjana, Hendrik P. Lopuhaä, Svetlana Borovkova

Publication date: 16 July 2024

Published in: Statistica Neerlandica (Search for Journal in Brave)

zbMATH Keywords

central limit theoremleast squares estimatormultivariate time serieslaw of large numbers for dependent sequencesspace-time autoregressive models

Mathematics Subject Classification ID

Linear inference, regression (62Jxx) Inference from stochastic processes (62Mxx) Limit theorems in probability theory (60Fxx)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A Three-Stage Iterative Procedure for Space-Time Modeling
• Strong consistency of least squares estimators in linear regression models
• Propriétés asymptotiques presque sûres de l'estimateur des moindres carrés d'un modèle autorégressif vectoriel. (Almost sure asymptotic properties of the least squares estimators in a vectorial autoregressive model)
• Asymptotic distributions of regression and autoregression coefficients with martingale difference disturbances
• Strong consistency of least squares estimates in dynamic models
• Aggregation of space-time processes.
• Maximum likelihood estimation of a generalized star(p; 1p) model
• Estimation and Identification of Space-Time ARMAX Models in the Presence of Missing Data
• Identification and Interpretation of First Order Space-Time ARMA Models
• Stationarity and invertibility regions for low order starma models
• Least squares estimates in stochastic regression models with applications to identification and control of dynamic systems
• Geostatistical space-time models: a review

This page was built for publication: Consistency and asymptotic normality of least squares estimators in generalized STAR models