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Using R, please simulate continuous data for y, x1, x2, x3, x4, x5, x6 Make sure code actually runs without error. Augment the data by
Using R, please simulate continuous data for y, x1, x2, x3, x4, x5, x6
Make sure code actually runs without error.
Augment the data by considering all two-way interactions (xixj for i=j). That is your set of predictors will consist of x1,x2,,x6,x1x2,x1x3,, x5x6. Using cv.glmnet () in R package glmnet, we will fit an elastic net by searching over 11 values (0,0.1,0.2,0.3,,0.9,1) and using the built-in values of cv. glmnet(), find combination of (,) that corresponds to minimum crossvalidation error. Fit a final model using this optimum value of (,) and report the predictors (including the interaction terms, if any) that are retained (i.e., have non-zero coefficients) in the final modelStep by Step Solution
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