VGAM (version 0.7-10)

predict.vglm: 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, ...)

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 vector generalized linear model (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, predict.vlm, smartpred.

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=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="res"))
p1 = head(predict(fit, type="res", newdata=pneumo))
p2 = head(predict(fit, type="res", 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)