weighted.residuals
Compute Weighted Residuals
Computed weighted residuals from a linear model fit.
 Keywords
 regression
Usage
weighted.residuals(obj, drop0 = TRUE)
Arguments
Details
Weighted residuals are based on the deviance residuals, which for
a lm
fit are the raw residuals $Ri$
multiplied by $wi^0.5$, where $wi$ are the
weights
as specified in lm
's call.
Dropping cases with weights zero is compatible with
influence
and related functions.
Value

Numeric vector of length $n'$, where $n'$ is the number of
of non0 weights (
drop0 = TRUE
) or the number of
observations, otherwise.
See Also
residuals
, lm.influence
, etc.
Examples
library(stats)
## following on from example(lm)
all.equal(weighted.residuals(lm.D9),
residuals(lm.D9))
x < 1:10
w < 0:9
y < rnorm(x)
weighted.residuals(lmxy < lm(y ~ x, weights = w))
weighted.residuals(lmxy, drop0 = FALSE)
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