Open hirscht opened 2 years ago
Hi @hirscht, is it possible to share the data for debugging?
Unfortunately not. But what I can do is, to insert the last part of the message that I get directly before the error, by using details=TRUE in the function. As you can see, predictor176 (V176) is the last that is selected in step 67 (The maximum number of predictors that could be selected is 69 since I have 70 observations). At the section "Parameter estimates" in the message I get all the predictors selected so far (here I show only the first and the last one). Then the error comes and all of this info is unfortunately not stored in the object where it should be.
Forward Selection: Step 67
+ V176
Model Summary
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R 1.000 RMSE 0.000
R-Squared 1.000 Coef. Var 0.000
Adj. R-Squared 1.000 MSE 0.000
Pred R-Squared 1.000 MAE 0.000
-------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
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Sum of
Squares DF Mean Square F Sig.
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Regression 27438349.309 67 409527.602 4040865085942.93 0.0000
Residual 0.000 2 0.000
Total 27438349.309 69
------------------------------------------------------------------------------
Parameter Estimates
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model Beta Std. Error Std. Beta t Sig lower upper
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(Intercept) -19274.197 0.584 -32995.677 0.000 -19276.710 -19271.683
V156 40.156 0.000 0.074 284504.288 0.000 40.155 40.157
....
....
....
V176 0.000 0.000 0.000 11.908 0.007 0.000 0.000
---------------------------------------------------------------------------------------------------------
Error in Anova.lm(m) :
residual sum of squares is 0 (within rounding error)
Let me look into this and get back to you.
I´m using a large number of potential predictors (larger than the number of predictand values used) with ols_step_forward_p(...) to select the predictors that fulfill the condition set by the p value. This works for most of the cases when p is set to a relatively low value but sometimes I have an error:
Error in Anova.lm(m) : residual sum of squares is 0 (within rounding error)
This happens when too many potential predictors fulfill the condition set by the p-value, resulting in being selected by the method, which eventially leads to the residual sum of sqaures being zero (Rsquared=1.000). In this case, I only get the Error message above and the result of the selection before the error is lost (not stored in a ols_step_forward_p class object). Would it be possible to store the calculated values even if there is this error? What I would need the most is the list of the selected predictors (in the order of the selection).