R: Predictions from an lmList Object

predict.lmList {nlme} | R Documentation

## Predictions from an lmList Object

### Description

If the grouping factor corresponding to `object` is included in `newdata`, the data frame is partitioned according to the grouping factor levels; else, `newdata` is repeated for all `lm` components. The predictions and, optionally, the standard errors for the predictions, are obtained for each `lm` component of `object`, using the corresponding element of the partitioned `newdata`, and arranged into a list with as many components as `object`, or combined into a single vector or data frame (if `se.fit=TRUE`).

### Usage

    ## S3 method for class 'lmList'
    predict(object, newdata, subset, pool, asList, se.fit, ...)

### Arguments

`object` | an object inheriting from class `lmList`, representing a list of `lm` objects with a common model.
`newdata` | an optional data frame to be used for obtaining the predictions. All variables used in the `object` model formula must be present in the data frame. If missing, the same data frame used to produce `object` is used.
`subset` | an optional character or integer vector naming the `lm` components of `object` from which the predictions are to be extracted. Default is `NULL`, in which case all components are used.
`asList` | an optional logical value. If `TRUE`, the returned object is a list with the predictions split by groups; else the returned value is a vector. Defaults to `FALSE`.
`pool` | an optional logical value indicating whether a pooled estimate of the residual standard error should be used. Default is `attr(object, "pool")`.
`se.fit` | an optional logical value indicating whether pointwise standard errors should be computed along with the predictions. Default is `FALSE`.
`...` | some methods for this generic require additional arguments. None are used in this method.

### Value

a list with components given by the predictions (and, optionally, the standard errors for the predictions) from each `lm` component of `object`, a vector with the predictions from all `lm` components of `object`, or a data frame with columns given by the predictions and their corresponding standard errors.

### Author(s)

Jose Pinheiro and Douglas Bates bates@stat.wisc.edu

### See Also

`lmList`, `predict.lm`

### Examples

    fm1 <- lmList(distance ~ age | Subject, Orthodont)
    predict(fm1, se.fit = TRUE)

[Package nlme version 3.1-104 Index]