Results 1 to 10 of about 21,030 (245)
Regression, Multicollinearity and Markowitz
Roberto Ortiz +2 more
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A note on some new modifications of ridge estimators
Ridge estimator is an alternative to ordinary least square estimator when there is multicollinearity problem. There are many proposed estimators in literature.
Yasin Asar, Aşır Genç
doaj
Bagging-based heteroscedasticity-adjusted ridge estimators in the linear regression model
The existence of multicollinearity between independent variables and heteroscedastic error has a colossal impact on the performance of the ordinary least square (OLS) estimator and its covariance matrix.
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RIDGE REGRESSION AS A POLICY FORECASTING TOOL IN LOW-DATA ENVIRONMENTS: EVIDENCE FROM BANGLADESH
Forecasting economic development outcomes in low-data environments is a significant challenge in many developing countries. This study presents ridge regression as a solid alternative to ordinary least squares (OLS) for policy forecasting in situations ...
Syed Ishfaqul Bari
doaj
APPROXIMATE LEAST SQUARES ESTIMATION OF ONE FORM OF NON-ELEMENTARY MODULAR LINEAR REGRESSIONS
Background. The problem of finding new structural specifications of regression models with interesting interpretive properties is currently relevant.
M.P. Bazilevskiy
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AbstractMulticollinearity refers to the linear relation among two or more variables. It is a data problem which may cause serious difficulty with the reliability of the estimates of the model parameters. In this article, multicollinearity among the explanatory variables in the multiple linear regression model is considered.
Aylin Alin
exaly +10 more sources
Some of the next articles are maybe not open access.
2011
Radi se o enciklopedijskoj natuknici na jednoj stranici sa 4 reference. Natuknica je prikazana na str. 869-870 u 13. dijelu "International Encyclopedia of Statistical Science" (Springer, 2011)
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Radi se o enciklopedijskoj natuknici na jednoj stranici sa 4 reference. Natuknica je prikazana na str. 869-870 u 13. dijelu "International Encyclopedia of Statistical Science" (Springer, 2011)
openaire +4 more sources

