predict.vglm {VGAM}R Documentation

Predict Method for a VGLM fit

Description

Predicted values based on a vector generalized linear model (VGLM) object.

Usage

predict.vglm(object, newdata = NULL, 
             type = c("link", "response", "terms"), 
             se.fit = FALSE, deriv = 0, dispersion = NULL,
             untransform=FALSE, extra = object@extra, ...)

Arguments

object Object of class inheriting from "vlm".
newdata An optional data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used.
type the type of prediction required. The default is the first one, meaning on the scale of the linear predictors. The alternative "response" is on the scale of the response variable, and depending on the family function, this may or may not be the mean. The "terms" option returns a matrix giving the fitted values of each term in the model formula on the linear predictor scale.
The value of this argument can be abbreviated.
se.fit logical: return standard errors?
deriv Non-negative integer. Currently this must be zero. Later, this may be implemented for general values.
dispersion Dispersion parameter. This may be inputted at this stage, but the default is to use the dispersion parameter of the fitted model.
extra A list containing extra information. This argument should be ignored.
untransform Logical. Reverses any parameter link function. This argument only works if type="link", se.fit=FALSE, deriv=0.
... Arguments passed into predict.vlm.

Details

Obtains predictions and optionally estimates standard errors of those predictions from a fitted vector generalized linear model (VGLM) object.

This code implements smart prediction (see smartpred).

Value

If se.fit = FALSE, a vector or matrix of predictions. If se.fit = TRUE, a list with components

fitted.values Predictions
se.fit Estimated standard errors
df Degrees of freedom
sigma The square root of the dispersion parameter

Warning

This function may change in the future.

Note

Setting se.fit=TRUE and type="response" will generate an error.

Author(s)

Thomas W. Yee

References

Yee, T. W. and Hastie, T. J. (2003) Reduced-rank vector generalized linear models. Statistical Modelling, 3, 15–41.

See Also

predict, vglm, predict.vlm, smartpred.

Examples

# Illustrates smart prediction
data(pneumo)
pneumo = transform(pneumo, let=log(exposure.time))
fit = vglm(cbind(normal,mild, severe) ~ poly(c(scale(let)), 2),
           fam=cumulative(parallel=TRUE),
           data=pneumo, trace=TRUE, x=FALSE)
class(fit)

(q0 = predict(fit)[1:3,])
(q1 = predict(fit, newdata=pneumo)[1:3,])
(q2 = predict(fit, newdata=pneumo[1:3,]))
all.equal(q0, q1)  # Should be TRUE
all.equal(q1, q2)  # Should be TRUE

predict(fit)[1:3,]
predict(fit, untransform=TRUE)[1:3,]

p0 = predict(fit, type="res")[1:3,]
p1 = predict(fit, type="res", newdata=pneumo)[1:3,]
p2 = predict(fit, type="res", newdata=pneumo[1:3,])
p3 = fitted(fit)[1:3,]
all.equal(p0, p1)  # Should be TRUE
all.equal(p1, p2)  # Should be TRUE
all.equal(p2, p3)  # Should be TRUE

predict(fit, type="t", se=TRUE)

[Package VGAM version 0.7-7 Index]