# residuals.ols

##### Residuals for ols

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

.

- Keywords
- models, regression

##### 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

##### See Also

##### 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)
# }
```

*Documentation reproduced from package rms, version 5.1-3.1, License: GPL (>= 2)*