Learn R Programming

VGAM (version 1.0-2)

predictvglm: Predict Method for a VGLM fit

Description

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

Usage

predictvglm(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", e.g., vglm.

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 value of this argument can be abbreviated. The type of prediction required. The default is the first one, meaning on the scale of the linear predictors. This should be a $n x M$ matrix.

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. Often this is the fitted value, e.g., fitted(vglmObject) (see fittedvlm). Note that the response is output from the @linkinv slot, where the eta argument is the $n x M$ matrix of linear predictors.

The "terms" option returns a matrix giving the fitted values of each term in the model formula on the linear predictor scale. The terms have been centered.

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. Setting untransform = TRUE does not work for all VGAM family functions; only ones where there is a one-to-one correspondence between a simple link function and a simple parameter might work.

...
Arguments passed into predictvlm.

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.

Details

Obtains predictions and optionally estimates standard errors of those predictions from a fitted vglm object.

This code implements smart prediction (see smartpred).

References

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

See Also

predict, vglm, predictvlm, smartpred.

Examples

Run this code
# Illustrates smart prediction
pneumo <- transform(pneumo, let = log(exposure.time))
fit <- vglm(cbind(normal, mild, severe) ~ poly(c(scale(let)), 2),
            propodds, data = pneumo, trace = TRUE, x.arg = FALSE)
class(fit)

(q0 <- head(predict(fit)))
(q1 <- predict(fit, newdata = head(pneumo)))
(q2 <- predict(fit, newdata = head(pneumo)))
all.equal(q0, q1)  # Should be TRUE
all.equal(q1, q2)  # Should be TRUE

head(predict(fit))
head(predict(fit, untransform = TRUE))

p0 <- head(predict(fit, type = "response"))
p1 <- head(predict(fit, type = "response", newdata = pneumo))
p2 <- head(predict(fit, type = "response", newdata = pneumo))
p3 <- head(fitted(fit))
all.equal(p0, p1)  # Should be TRUE
all.equal(p1, p2)  # Should be TRUE
all.equal(p2, p3)  # Should be TRUE

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

Run the code above in your browser using DataLab