Asymptotic confidence intervals in ridge regression based on the Edgeworth expansion |
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Authors: | Luis Firinguetti Gladys Bobadilla |
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Institution: | (1) Baxter Innovations GmbH, Vienna, Austria;(2) Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom |
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Abstract: | Ridge Regression techniques have been found useful to reduce mean square errors of parameter estimates when multicollinearity
is present. But the usefulness of the method rest not only upon its ability to produce good parameter estimates, with smaller
mean squared error than Ordinary Least Squares, but also on having reasonable inferential procedures. The aim of this paper
is to develop asymptotic confidence intervals for the model parameters based on Ridge Regression estimates and the Edgeworth
expansion. Some simulation experiments are carried out to compare these confidence intervals with those obtained from the
application of Ordinary Least Squares. Also, an example will be provided based on the well known data set of Hald. |
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