quanteda (version 1.5.2)

predict.textmodel_wordscores: Predict textmodel_wordscores

Description

Predict textmodel_wordscores

Usage

# S3 method for 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 predict.lm.

Examples

# NOT RUN {
tmod <- textmodel_wordscores(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")
# }

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