preproc: Optional preprocessing step for regressing out noise...
In detectR: Change Point Detection
preproc R Documentation
Optional preprocessing step for regressing out noise variables.
Description
This function saves the residuals after regressing the user-defined
noise variables from the user-defined "signal" variables. Noise variables can
be nuisance regressors (such as cebral spinal fluid in fMRI), time vectors,
or any other vector that the user wishes to regress out.
Usage
preproc(Y, noise, signal)
Arguments
Y
data: Y = length*dim
noise
string vector indicating which variables (columns) are regressors
signal
string vector indicating which variables to regress out the noise variables from
Value
signalmatrix
detectR documentation built on June 22, 2024, 12:23 p.m.
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| preproc | R Documentation |
Optional preprocessing step for regressing out noise variables.
Description
This function saves the residuals after regressing the user-defined noise variables from the user-defined "signal" variables. Noise variables can be nuisance regressors (such as cebral spinal fluid in fMRI), time vectors, or any other vector that the user wishes to regress out.
Usage
preproc(Y, noise, signal)
Arguments
Y |
data: Y = length*dim |
noise |
string vector indicating which variables (columns) are regressors |
signal |
string vector indicating which variables to regress out the noise variables from |
Value
signalmatrix
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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