R: Predict textmodel_wordscores

predict.textmodel_wordscores {quanteda.textmodels} | R Documentation

## Predict textmodel_wordscores

### Description

Predict textmodel_wordscores

### Usage

    ## S3 method for class 'textmodel_wordscores'
    predict(
      object,
      newdata = NULL,
      se.fit = FALSE,
      interval = c("none", "confidence"),
      level = 0.95,
      rescaling = c("none", "lbg", "mv"),
      force = TRUE,
      ...
    )

### Arguments

`object` | a fitted Wordscores textmodel
`newdata` | dfm on which prediction should be made
`se.fit` | if `TRUE`, return standard errors as well
`interval` | type of confidence interval calculation
`level` | tolerance/confidence level for intervals
`rescaling` | `"none"` for "raw" scores; `"lbg"` for LBG (2003) rescaling; or `"mv"` for the rescaling proposed by Martin and Vanberg (2007). See References.
`force` | make the feature set of `newdata` conform to the model terms. The default of `TRUE` means that a fitted model can be applied to scale a dfm that does not contain a 1:1 match of features in the training and prediction data.
`...` | not used

### Value

`predict.textmodel_wordscores()` returns a named vector of predicted document scores ("text scores" S_{vd} in LBG 2003), or a named list if `se.fit = TRUE` consisting of the predicted scores (`$fit`) and the associated standard errors (`$se.fit`). When `interval = "confidence"`, the predicted values will be a matrix. This behaviour matches that of `stats::predict.lm()`.

### Examples

    tmod <- textmodel_wordscores(quanteda::data_dfm_lbgexample, c(seq(-1.5, 1.5, .75), NA))
    predict(tmod)
    predict(tmod, rescaling = "mv")
    predict(tmod, rescaling = "lbg")
    predict(tmod, se.fit = TRUE)
    predict(tmod, se.fit = TRUE, interval = "confidence")
    predict(tmod, se.fit = TRUE, interval = "confidence", rescaling = "lbg")

[Package quanteda.textmodels version 0.9.4 Index]