# 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 \(R_i\)
multiplied by \(\sqrt{w_i}\), where \(w_i\) 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 non-0 weights (`drop0 = TRUE`

) or the number of
observations, otherwise.

##### See Also

`residuals`

, `lm.influence`

, etc.

##### Examples

`library(stats)`

```
# NOT RUN {
## following on from example(lm)
# }
# NOT RUN {
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)
# }
```

*Documentation reproduced from package stats, version 3.5.0, License: Part of R 3.5.0*

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