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

### See Also

`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]