PseudoInverseSolution_percell: Network-based parallel imputation - Moore-Penrose...
In anacarolinaleote/ADImpute: Adaptive Dropout Imputer (ADImpute)
Description
Usage
Arguments
Value
View source: R/NetworkFunctions.R
Description
PseudoInverseSolution_percell applies Moore-Penrose
pseudo-inversion to compute the solution of network imputation for each
cell
Usage
1
PseudoInverseSolution_percell(expr, net, drop_ind, thr = 0.01)
Arguments
expr
numeric; expression vector for cell at hand
net
matrix; network coefficients
drop_ind
logical; dropout entries in the cell at hand
thr
numeric; tolerance threshold to detect zero singular values
Value
matrix; imputation results incorporating network information
anacarolinaleote/ADImpute documentation built on May 18, 2021, 10:11 p.m.
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Description Usage Arguments Value
View source: R/NetworkFunctions.R
Description
PseudoInverseSolution_percell applies Moore-Penrose
pseudo-inversion to compute the solution of network imputation for each
cell
Usage
1 | PseudoInverseSolution_percell(expr, net, drop_ind, thr = 0.01)
|
Arguments
expr |
numeric; expression vector for cell at hand |
net |
matrix; network coefficients |
drop_ind |
logical; dropout entries in the cell at hand |
thr |
numeric; tolerance threshold to detect zero singular values |
Value
matrix; imputation results incorporating network information
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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