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Regression quantiles and trimmed least squares estimators for structural equations and nonlinear regression model

Posted on:1989-01-31Degree:Ph.DType:Thesis
University:University of Illinois at Urbana-ChampaignCandidate:Chen, Lin-anFull Text:PDF
GTID:2470390017455650Subject:Statistics
Abstract/Summary:
This thesis extends some robust estimation techniques to the structural equation model and nonlinear regression model. Bahadur representations and limiting distributions for regression quantiles and trimmed least squares estimators based on regression quantiles have been derived for both regression models. In addition, some asymptotic properties for a trimmed least squares estimator based on the quantiles of residurals of a predetermined estimator for the structural equation models has also been derived.
Keywords/Search Tags:Structural equation, Nonlinear regression model, Trimmed least squares, Quantiles
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