On Validating Regression Models with Bootstraps and Data Splitting Techniques

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Provided by: Global Journals
Topic: Data Management
Format: PDF
Model validity is the stability and reasonableness of the regression coefficients, the plausibility and usability of the regression function and ability to generalize inference drawn from the regression analysis. Model validation is an important step in the modeling process and helps in assessing the reliability of models before they can be used in decision making. Therefore, this paper seeks to study regression model validation process by bootstrapping approach and data splitting techniques. The authors review regression model validation by comparing predictive index accuracy of data splitting techniques and residual resampling bootstraps.
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