na.handling {siggenes} R Documentation

## Handling of Missing Values

### Description

Removes missing values from a data set either by replacing them or by removing the rows that contain missing values.

### Usage

```  na.handling(X, na.replace = TRUE, na.method = "mean")
```

### Arguments

 `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"`

### Details

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`.

### Value

 `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`

### Author(s)

Holger Schwender, holger.schw@gmx.de

`na.replace.cont`,`na.replace.dist`

### Examples

```   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)
```

[Package siggenes version 1.4.0 Index]