rms (version 5.1-3.1)

# residuals.ols: Residuals for ols

## Description

Computes various residuals and measures of influence for a fit from `ols`.

## Usage

```# S3 method for ols
residuals(object,
type=c("ordinary", "score", "dfbeta", "dfbetas",
"dffit", "dffits", "hat", "hscore"), …)```

## Arguments

object

object created by `ols`. Depending on `type`, you may have had to specify `x=TRUE` to `ols`.

type

type of residual desired. `"ordinary"` refers to the usual residual. `"score"` is the matrix of score residuals (contributions to first derivative of log likelihood). `dfbeta` and `dfbetas` mean respectively the raw and normalized matrix of changes in regression coefficients after deleting in turn each observation. The coefficients are normalized by their standard errors. `hat` contains the leverages --- diagonals of the ``hat'' matrix. `dffit` and `dffits` contain respectively the difference and normalized difference in predicted values when each observation is omitted. The S `lm.influence` function is used. When `type="hscore"`, the ordinary residuals are divided by one minus the corresponding hat matrix diagonal element to make residuals have equal variance.

ignored

## Value

a matrix or vector, with places for observations that were originally deleted by `ols` held by `NA`s

`lm.influence`, `ols`, `which.influence`

## Examples

```# NOT RUN {
set.seed(1)
x1 <- rnorm(100)
x2 <- rnorm(100)
x1[1] <- 100
y <- x1 + x2 + rnorm(100)
f <- ols(y ~ x1 + x2, x=TRUE, y=TRUE)
resid(f, "dfbetas")
which.influence(f)
# }
```