milr.predict.Rd
This function computes a prediction or low-dimensional embedding, given
milr
output. It will return a predictive model if the outcome variable
is a scalar. Otherwise, it will return a low-dimensional embedding without
a specific predictive model.
milr.predict( milrResult, dataFrameTrain, voxmatsTrain, dataFrameTest, voxmatsTest, myFormula )
milrResult | This output form milr |
---|---|
dataFrameTrain | This data frame contains all relevant predictors in the training data except for the matrices associated with the image variables. |
voxmatsTrain | The named list of matrices that contains the changing predictors. |
dataFrameTest | This data frame contains all relevant predictors in the training data except for the matrices associated with the image variables in test data. |
voxmatsTest | The named list of matrices that contains the changing predictors in test data. |
myFormula | This is a character string that defines a valid regression formula. |
the predicted matrix.
BB Avants.
nsub = 24 npix = 100 outcome = rnorm( nsub ) covar = rnorm( nsub ) mat = replicate( npix, rnorm( nsub ) ) mat2 = replicate( npix, rnorm( nsub ) ) mat3 = replicate( npix, rnorm( nsub ) ) myform = " vox2 ~ covar + vox + vox3 " istr = c( rep( TRUE, round(nsub*2/3) ), rep( FALSE, nsub - round(nsub*2/3)) ) df = data.frame( outcome = outcome, covar = covar ) ltr = list( vox = mat[ istr,], vox2 = mat2[istr,], vox3 = mat3[istr,] ) lte = list( vox = mat[!istr,], vox2 = mat2[!istr,], vox3 = mat3[!istr,] ) result = milr( df[istr,], ltr, myform) pred = milr.predict( result, df[istr,],ltr, df[!istr,], lte, myform )