R: Adjust for Missing Values

naresid {stats} | R Documentation

## Adjust for Missing Values

### Description

Use missing value information to adjust residuals and predictions.

### Usage

    naresid(omit, x, ...)
    napredict(omit, x, ...)

### Arguments

`omit` | an object produced by an `na.action` function, typically the `"na.action"` attribute of the result of `na.omit` or `na.exclude`.
`x` | a vector, data frame, or matrix to be adjusted based upon the missing value information.
`...` | further arguments passed to or from other methods.

### Details

These are utility functions used to allow `predict`, `fitted` and `residuals` methods for modelling functions to compensate for the removal of `NA`s in the fitting process. They are used by the default, `"lm"`, `"glm"` and `"nls"` methods, and by further methods in packages MASS, rpart and survival. Also used for the scores returned by `factanal`, `prcomp` and `princomp`.

The default methods do nothing. The default method for the `na.exclude` action is to pad the object with `NA`s in the correct positions to have the same number of rows as the original data frame.

Currently `naresid` and `napredict` are identical, but future methods need not be. `naresid` is used for residuals, and `napredict` for fitted values, predictions and `weights`.

### Value

These return a similar object to `x`.

### Note

In the early 2000s, packages rpart and survival5 contained versions of these functions that had an `na.omit` action equivalent to that now used for `na.exclude`.

[Package stats version 3.5.1 Index]