View source: R/multiscaleSVDxpts.R
milr.predict | R Documentation |
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.
milr
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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.