predict.regr: Prediction Methods for 'regr' Objects

In regr: Building Regression Models

Description

Calculates predicted values for regr objects. The possible results depend on the class of the fitted model.

Usage

## S3 method for class 'regr'
predict(object, newdata = NULL, scale = object$sigma,
  df=object$df.residual, type = NULL, ...)




## 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, ...)

Arguments

object	Object of class regr
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 For glm or ordered regression, type link gives estimated values of the linear predictor.
terms	If type="terms", which terms (default is all terms)
na.action	function determining what should be done with missing values in newdata. The default is to insert NA.
pred.var, weights	see lm
...	further arguments passed to specific methods

Details

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.

Value

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

Author(s)

Werner A. Stahel, ETH Zurich

See Also

predict.lm, fitted.polr

Examples

data(d.blast, package="plgraphics")
r.blast <- regr(log10(tremor)~location+log10(distance)+log10(charge),
            data=d.blast)
t.pr <- predict(r.blast)
plgraphics::showd(t.pr)

data(d.fossileSamples, package="plgraphics")
r.mregr <-
  regr(cbind(sAngle,lLength,rWidth)~SST+Salinity+lChlorophyll+Region+N,
                data=d.fossileSamples)
t.pr <- predict(r.mregr)
plgraphics::showd(t.pr)

regr documentation built on Oct. 22, 2019, 3:01 p.m.