A class of generalized shrunken least squares estimators in linear model
Modern data analysis often involves a large number of variables, which gives rise to the problem of multicollinearity in regression models. It is well-known that in a linear model, when the design matrix X is nearly singular, then the ordinary least squares (OLS) estimator may perform poorly because...
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| Language: | en_US |
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2010
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| Online Access: | http://hdl.handle.net/1993/4188 |