On Developing Ridge Regression Parameters: A Graphical investigation
AbstractIn this paper we have reviewed some existing and proposed some new estimators for estimating the ridge parameter "k" . All in all 19 different estimators have been studied. The investigation has been carried out using Monte Carlo simulations. A large number of different models were investigated where the variance of the random error, the number of variables included in the model, the correlations among the explanatory variables, the sample size and the unknown coefficients vectors "beta" have been varied. For each model we have performed 2000 replications and presented the results both in term of figures and tables. Based on the simulation study, we found that increasing the number of correlated variable, the variance of the random error and increasing the correlation between the independent variables have negative effect on the MSE. When the sample size increases the MSE decreases even when the correlation between the independent variables and the variance of the random error are large. In all situations, the proposed estimators have smaller MSE than the ordinary least squared and some other existing estimators.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by HUI Research in its series HUI Working Papers with number 29.
Length: 25 pages
Date of creation: 01 May 2009
Date of revision:
Contact details of provider:
Postal: HUI Research, Regeringsgatan 60, 103 29 Stockholm, Sweden
Phone: +46 (0)8 762 72 80
Fax: +46 (0)8 679 76 06
Web page: http://www.hui.se/
More information through EDIRC
Linear Model; LSE; MSE; Monte Carlo simulations; Multicollinearity; Ridge Regression;
Find related papers by JEL classification:
- F10 - International Economics - - Trade - - - General
You can help add them by filling out this form.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Helena Nilsson).
If references are entirely missing, you can add them using this form.