View source: R/combineNuisancePredictors.R
combineNuisancePredictors | R Documentation |
Combine and select nuisance predictors to maximize
correlation between inmat
and target
.
combineNuisancePredictors(
inmat,
target,
globalpredictors = NA,
maxpreds = 4,
localpredictors = NA,
method = "cv",
k = 5,
covariates = NA,
ordered = FALSE
)
inmat |
Input predictor matrix. |
target |
Target outcome matrix. |
globalpredictors |
Global predictors of size |
maxpreds |
Maximum number of predictors to output. |
localpredictors |
Local predictor array of size |
method |
Method of selecting noisy voxels. One of 'svd' or 'cv'.
See |
k |
Number of cross-validation folds. |
covariates |
Covariates to be considered when assessing prediction
of |
ordered |
Can the predictors be assumed to be ordered from most important to least important, as in output from PCA? Computation is much faster if so. |
Array of size nrow(aslmat)
by npreds
,
containing a timeseries of all the nuisance predictors.
If localpredictors
is not NA, array is of size nrow(aslmat)
by ncol(aslmat)
by npreds
.
Benjamin M. Kandel, Brian B. Avants
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