| na.handling {siggenes} | R Documentation |
Removes missing values from a data set either by replacing them or by removing the rows that contain missing values.
na.handling(X, na.replace = TRUE, na.method = "mean")
X |
a matrix |
na.replace |
If TRUE, missing values are replaced by
the rowwise statistic specified by na.method. If
FALSE, all rows with one or more missing values are
removed |
na.method |
character string specifying the statistic
with which the missing values should be replaced. Must be either
"mean" or "median" |
Since missing values are replaced by either the rowwise mean or median,
na.handling can only handle continuous data. There is, however, no
check if the data is continuous or categorical/discrete.
If there are no or only one non-missing value in a row, na.handling
will remove this row from the data set even if na.replace=TRUE.
X |
matrix without missing values. The number of rows of X can
differ from the number of rows of the input matrix X, since all
rows with either less than one non-missing value (if na.replace=TRUE)
or with at least one missing value (if na.replace=FALSE) are
removed |
NA.genes |
the rows of the input matrix X that are removed and
thus are excluded from the output matrix X |
Holger Schwender, holger.schw@gmx.de
na.replace.cont,na.replace.dist
mat<-matrix(1:20,5,4) mat[1,2]<-NA mat # Replace the missing value by the mean of the first row. na.handling(mat) # Remove the first row. na.handling(mat,na.replace=FALSE) # Replace the missing value in the first row by the mean of # this row, and remove the second row containing only NAs. mat[2,]<-NA mat na.handling(mat)