R: Predict Method for a VGLM fit

predictvglm {VGAM}

R Documentation

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`.

Details

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

Examples

# 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)

[Package VGAM version 1.0-1 Index]