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
    pneumo = transform(pneumo, let=log(exposure.time))
    fit = vglm(cbind(normal,mild, severe) ~ poly(c(scale(let)), 2),
               cumulative(parallel=TRUE),
               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)

[Package VGAM version 0.7-9 Index]