Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
Communities & Collections
Communities & Collections
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Comparison of regression techniques via Monte Carlo simulation
Download
index.pdf
Date
2004
Author
Mutan, Oya Can
Metadata
Show full item record
The ordinary least squares (OLS) is one of the most widely used methods for modelling the functional relationship between variables. However, this estimation procedure counts on some assumptions and the violation of these assumptions may lead to nonrobust estimates. In this study, the simple linear regression model is investigated for conditions in which the distribution of the error terms is Generalised Logistic. Some robust and nonparametric methods such as modified maximum likelihood (MML), least absolute deviations (LAD), Winsorized least squares, least trimmed squares (LTS), Theil and weighted Theil are compared via computer simulation. In order to evaluate the estimator performance, mean, variance, bias, mean square error (MSE) and relative mean square error (RMSE) are computed.
Subject Keywords
Probabilities.
URI
http://etd.lib.metu.edu.tr/upload/3/12605175/index.pdf
https://hdl.handle.net/11511/14278
Collections
Graduate School of Natural and Applied Sciences, Theses
