Selecting a Regression Saturated by Indicators
Research output: Working paper
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Final published version, 192 KB, PDF document
We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest
Original language | English |
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Publisher | Department of Economics, University of Copenhagen |
Number of pages | 17 |
Publication status | Published - 2007 |
- Faculty of Social Sciences - indicators, regression saturation, subset selection, model selection
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ID: 1523856