Estimation in autoregressive models with surrogate data and validation data

DOI10.1080/03610926.2015.1019154zbMath1360.62096OpenAlexW2329069123MaRDI QIDQ2979624

No author found.

Publication date: 25 April 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2015.1019154

zbMATH Keywords

asymptotic normalityautoregressionerror in variablesvalidation data

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Point estimation (62F10)

Cites Work

• Unnamed Item
• Unnamed Item
• Asymptotic normality and strong consistency of maximum quasi-likelihood estimates in generalized linear models
• Improvement on some known nonparametric uniformly consistent estimators of derivatives of a density
• Estimation of partial linear error-in-variables models with validation data
• Estimation of linear error-in-covariables models with validation data under random censorship
• The Application of Time Series Methods to the Analysis of Repeated Surveys
• Empirical likelihood-based inference in linear errors-in-covariables models with validation data
• Semiparametric estimation of nonlinear errors-in-variables models with validation study
• A mean score method for missing and auxiliary covariate data in regression models
• Central limit theorems for martingales and for processes with stationary increments using a Skorokhod representation approach

This page was built for publication: Estimation in autoregressive models with surrogate data and validation data