Validating Regression Procedures with New Data

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Abstract
The best way to validate the predictive ability of a statistical model is to apply it to new data. This article compares eight ways to form regression models by forming them with old data and then validating them with fresh data. One goal here is to study which methods will work as a function of the type of data. To some extent one can tell which methods will work well by looking at the data. Another goal is to study the quality of prediction when the regression is applied to new data. Prediction quality is determined in large part by the distance of the new data in relation to the old.

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