Third-order inference for autocorrelation in nonlinear regression models

DOI10.1016/j.jspi.2011.04.019zbMath1221.62102OpenAlexW2016381959MaRDI QIDQ2276174

P. E. Nguimkeu, Marie Rekkas

Publication date: 1 August 2011

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2011.04.019

zbMATH Keywords

\(p\)-valuelikelihood analysis

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric hypothesis testing (62F03) Hypothesis testing in multivariate analysis (62H15) General nonlinear regression (62J02) Monte Carlo methods (65C05) Mathematical geography and demography (91D20)

Related Items (2)

Improved inference for moving average disturbances in nonlinear regression models ⋮ Improved likelihood-based inference in Birnbaum-Saunders nonlinear regression models

Cites Work

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• Improved likelihood-based inference for the stationary AR(2) model
• Improved inference for first-order autocorrelation using likelihood analysis
• Modified signed log likelihood ratio
• Probit with Dependent Observations
• Saddle point approximation for the distribution of the sum of independent random variables
• Statistical Inference in an Implicit, Nonlinear, Simultaneous Equation Mode in the Context of Maximum Likelihood Estimation
• Testing for Autocorrelated Disturbances in Nonlinear Regression Analysis
• The Maximum Likelihood and the Nonlinear Three-Stage Least Squares Estimator in the General Nonlinear Simultaneous Equation Model
• A simple general formula for tail probabilities for frequentist and Bayesian inference

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