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Unformatted text preview: 1. Start with k = 0 and i = 1. For the model with k p factors, at step i , the i th observation is removed. 2. The k components are extracted and the regression is t on the remaining data. 3. The predicted value for the left out point is calculated. 4. Repeat steps 1-3 on all points. 5. The dierence between the sum of squared predicted residuals for the model with k compo-nents and the sum of squared predicted residuals for the minimizing model is calculated. 6. Repeat steps i-v on all models with k p factors, and 1 i n , and choose the model with the smallest number of factors that is signicantly dierent from the minimizing model. 1...
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This note was uploaded on 07/14/2011 for the course STA 4702 taught by Professor Staff during the Spring '08 term at University of Florida.
- Spring '08