Host Institution: |
La Trobe University |
Title of Seminar: |
Confidence sets for variable selection |
Speaker's Name: |
Dr Davide Ferrari |
Speaker's Institution: |
The University of Melbourne |
Time and Date: |
Friday 13 September, 1.00pm (AEST) |
Seminar Abstract: |
We introduce the notion of variable selection confidence set (VSCS) for linear regression based on F-testing. The VSCS extends the usual notion of confidence intervals to the variable selection problem: A VSCS is a set of regression models that contains the true model with a given level of confidence. For noisy data, distinguishing among competing models is usually very difficult and the VSCS will contain many models; if the data are really informative, the VSCS will contain a much smaller number of useful models. We advocate special attention to the set of lower boundary models (LBMs), which are the most parsimonious models that are not statistically significantly inferior to the full model at a given confidence level. Based on the LBMs, variable importance and measures of co-appearance importance of predictors can be naturally defined. |
Seminar Contact: |
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AGR Support: |
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