Abstract
As it is well known, Ridge Regression can be a useful technique for estimating the coefficients of a Multiple Regression Model in the presence of multicollinearity. It has, however, the drawback that the distribution of the estimator is unknown, so that only asymptotic confidence intervals may be obtained. The aim of this paper is to report on the use of a technique that combines the Bootstrap and the Edgeworth Expansion to obtain an approximation to the distribution of some Ridge Regression estimators. Some simulation experiments were carried out to compare the asymptotic confidence intervals with those obtained with this technique
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