| residuals.ols {Design} | R Documentation |
Computes various residuals and measures of influence for a
fit from ols.
## S3 method for class 'ols':
residuals(object,
type=c("ordinary", "score", "dfbeta", "dfbetas",
"dffit", "dffits", "hat", "hscore"), ...)
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 |
a matrix or vector, with places for observations that were originally
deleted by ols held by NAs
Frank Harrell
Department of Biostatistics
Vanderbilt University
f.harrell@vanderbilt.edu
lm.influence, ols, which.influence, naresid
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)