Minimum distance estimation in linear models with long-range dependent errors

DOI10.1016/0167-7152(94)00029-8zbMath0806.62071OpenAlexW2011106094MaRDI QIDQ1341366

Kanchan Mukherjee

Publication date: 9 January 1995

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(94)00029-8

zbMATH Keywords

Hermite polynomialslimiting distributionsasymptotic representationsweighted empirical processesgoodness of fit testsHermite ranklong-range dependentmultiple linear regression modelasymptotic uniform quadraticitystationary Gaussian random variablesL2-distance estimators

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05)

Related Items (2)

\(M\)-estimation for dependent random variables ⋮ Asymptotics of minimum distance estimator in linear regression models under strong mixing

Cites Work

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• On estimation of a regression model with long-memory stationary errors
• Asymptotics of R-, MD- and LAD-estimators in linear regression models with long range dependent errors
• The ``automatic robustness of minimum distance functionals
• The Minimum Distance Method
• Robust estimation via minimum distance methods
• Minimum Distance Estimators for Location and Goodness of Fit
• Minimum Distance and Robust Estimation
• AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
• Weak convergence to fractional brownian motion and to the rosenblatt process

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