<--- Back to Details
First PageDocument Content
Estimation theory / Least squares / Parametric statistics / Linear regression / Bias of an estimator / Gauss–Markov theorem / Mean squared error / Multicollinearity / Variance / Statistics / Regression analysis / Econometrics
Date: 2013-01-11 21:49:51
Estimation theory
Least squares
Parametric statistics
Linear regression
Bias of an estimator
Gauss–Markov theorem
Mean squared error
Multicollinearity
Variance
Statistics
Regression analysis
Econometrics

Robust strategies and model selection

Add to Reading List

Source URL: www.cfe-csda.org

Download Document from Source Website

File Size: 2,26 MB

Share Document on Facebook

Similar Documents

Perspectival Variance and Worldly Fragmentation Martin A. Lipman Objects often manifest themselves in incompatible ways across perspectives that are epistemically on a par. The standard response to such cases is to deny

DocID: 1vrXP - View Document

Microsoft WordAPP Variance

DocID: 1vrre - View Document

IETF Trust Statement of Activity For the Month Ending March 31, 2017 March YTD Actual YTD Budget YTD Variance Annual Budget Notes

DocID: 1voPG - View Document

LAKE SHASTINA PROPERTY OWNERS ASSOCIATIONEverhart Drive Weed CaVoiceFaxApplication # ____________ APPLICATION FOR VARIANCE DATE __________________

DocID: 1vo6V - View Document

Portfolios & Systematic Risk Expected Return and Variance of a Portfolio E(R)=ΣwiE(ri) V(R)=ΣΣwiwjCov(ri,rj) The Variance Contributed by Stock i ΣwjCov(ri,rj) =Cov(ri,Σwjr)

DocID: 1vnjW - View Document