imputeBetasMatrixByMean: Impute Missing Values with Mean This function replaces...
In zwdzwd/sesame: SEnsible Step-wise Analysis of DNA MEthylation BeadChips
imputeBetasMatrixByMean R Documentation
Impute Missing Values with Mean
This function replaces missing values (NA) in a matrix, default is row
means.
Description
Impute Missing Values with Mean
This function replaces missing values (NA) in a matrix, default is row
means.
Usage
imputeBetasMatrixByMean(mx, axis = 1)
Arguments
mx
A matrix
axis
A single integer. Use 1 to impute column means (default),
and 2 to impute row means.
Value
A matrix with missing values imputed.
Examples
mx <- cbind(c(1, 2, NA, 4), c(NA, 2, 3, 4))
imputeBetasMatrixByMean(mx, axis = 1)
imputeBetasMatrixByMean(mx, axis = 2)
zwdzwd/sesame documentation built on Dec. 21, 2024, 1:20 p.m.
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| imputeBetasMatrixByMean | R Documentation |
Impute Missing Values with Mean This function replaces missing values (NA) in a matrix, default is row means.
Description
Impute Missing Values with Mean This function replaces missing values (NA) in a matrix, default is row means.
Usage
imputeBetasMatrixByMean(mx, axis = 1)
Arguments
mx |
A matrix |
axis |
A single integer. Use 1 to impute column means (default), and 2 to impute row means. |
Value
A matrix with missing values imputed.
Examples
mx <- cbind(c(1, 2, NA, 4), c(NA, 2, 3, 4))
imputeBetasMatrixByMean(mx, axis = 1)
imputeBetasMatrixByMean(mx, axis = 2)
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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