Description Usage Arguments Details Value Author(s) See Also Examples
Calculates predicted values for regr objects.
The possible results depend on the class of the fitted model.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## S3 method for class 'regr'
predict(object, newdata = NULL, scale = object$sigma,
df=object$df.residual, type = NULL, ...)
## S3 method for class 'polr'
predict(object, newdata=NULL,
type = c("class", "probs", "link"), ...)
## S3 method for class 'mlm'
predict(object, newdata=NULL, se.fit = FALSE,
scale = NULL, df = Inf,
interval = c("none", "confidence", "prediction"), level = 0.95,
type = c("response", "terms"), terms = NULL, na.action = na.pass,
pred.var = NULL, weights = 1, ...)
|
object |
Object of class |
newdata |
An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used. |
se.fit |
if TRUE, standard errors will be calculated if possible |
scale |
Scale parameter for std.err. calculation |
df |
Degrees of Freedom to be used, for quantiles defining intervals |
interval |
Type of interval requested |
level |
Confidence level |
type |
Type of prediction: response or model term |
terms |
If |
na.action |
function determining what should be done with missing values
in |
pred.var, weights |
see |
... |
further arguments passed to specific methods |
regr is a "super class" which includes many specific model
classes such as "lm", "glm", "polr", ... .
predict.regr is a wrapper function that calls the specific methods
corresponding to the specific model class.
vector of predictions, or matrix with columns fit, lwr,
and upr if interval is set.
If se.fit is TRUE, a list with the
following components is returned:
fit |
vector or matrix as above |
se.fit |
standard error of predicted means |
residual.scale |
residual standard deviations |
df |
degrees of freedom for residual~Describe the value returned |
Werner A. Stahel, ETH Zurich
1 2 3 4 5 6 7 8 9 10 11 12 |
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