# residuals.ols

0th

Percentile

##### 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 NAs

lm.influence, ols, which.influence

##### Aliases
• residuals.ols
##### 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)

### Community examples

Looks like there are no examples yet.