matNSamp: Find the number of non-missing values.
In nosarcasm/DGCA: Differential Gene Correlation Analysis
Description
Usage
Arguments
Value
Description
This function calculates the pairwise number of non-missing values in a matrix.
Usage
1
Arguments
matA
Input data matrix with numeric entries.
impute
Binary value; if true, indicates that imputation was performed previously, and so checking for NAs is not necessary.
matB
Optional input data matrix with which the comparison with matA will be made.
secondMat
Logical indicator of whether there is a second matrix in the comparison or not.
Value
A number of samples (nsamp) matrix.
data(darmanis); darmanis_subset = as.matrix(darmanis[1:30, ])
nsamp_res = matNSamp(darmanis_subset)
darmanis_subset[1, 1] = NA
nsamp_res_na = matNSamp(darmanis_subset)
nosarcasm/DGCA documentation built on June 13, 2019, 11:49 p.m.
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Description Usage Arguments Value
Description
This function calculates the pairwise number of non-missing values in a matrix.
Usage
1 |
Arguments
matA |
Input data matrix with numeric entries. |
impute |
Binary value; if true, indicates that imputation was performed previously, and so checking for NAs is not necessary. |
matB |
Optional input data matrix with which the comparison with matA will be made. |
secondMat |
Logical indicator of whether there is a second matrix in the comparison or not. |
Value
A number of samples (nsamp) matrix. data(darmanis); darmanis_subset = as.matrix(darmanis[1:30, ]) nsamp_res = matNSamp(darmanis_subset) darmanis_subset[1, 1] = NA nsamp_res_na = matNSamp(darmanis_subset)
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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