A couple of methods for location-scale regression models from the lmls()
function are provided.
Usage
# S3 method for class 'lmls'
coef(object, predictor = c("location", "scale"), ...)
# S3 method for class 'lmls'
fitted(object, predictor = c("location", "scale"), ...)
# S3 method for class 'lmls'
predict(
object,
newdata = NULL,
predictor = c("location", "scale"),
type = c("link", "response"),
...
)
# S3 method for class 'lmls'
residuals(object, type = c("deviance", "pearson", "response"), ...)
# S3 method for class 'lmls'
vcov(object, predictor = c("location", "scale"), ...)Arguments
- object
A location-scale regression model from the
lmls()function.- predictor
The predictor to work on. Either
"location"or"scale"or both. If both, a list with the names"location"and"scale"is returned.- ...
Currently ignored.
- newdata
A data frame (or list or environment) with the covariate values at which the predictions are computed. If
NULL, the predictions at the original data are returned.- type
Used by
predict()andresiduals():For
predict(),"link"or"response". If"link"(default), \(\mu\) and log(\(\sigma\)) are returned. If"response", \(\mu\) and \(\sigma\) are returned.For
residuals(),"deviance","pearson"or"response". If"deviance"(default) or"pearson", (\(y - \mu\)) / \(\sigma\) is returned. If"response", \(y - \mu\) is returned.
Value
A numeric vector for residuals(). For the other methods, a numeric vector
if the argument predictor is either "location" or "scale", or a list
with the names location and scale if it is both.