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crch

predict.hxlr

Predict/Fitted Values for HXLR Fits

Description

Obtains various types of predictions/fitted values for heteroscedastic extended logistic regression (HXLR) models.

Usage

## S3 method for class 'hxlr'
predict(object, newdata = NULL, type = c("class", "probability",
  "cumprob", "location", "scale"), thresholds = object$thresholds,
  na.action = na.pass, ...)
## S3 method for class 'hxlr'
fitted(object, type = c("class", "probability", 
  "cumprob", "location", "scale"), ...)

Arguments

`object`	an object of class `"hxlr"`.
`newdata`	an optional data frame in which to look for variables with which to predict.
`type`	type of prediction: `"probability"` returns a data frame with category probabilities, `"cumprob"` returns cumulative probabilities, `"location"` and `"scale"` return the location and scale of the predicted latent distribution respectively, and `"class"` returns the category with the highest probability. Default is `"class"`.
`thresholds`	optional thresholds used for defining the thresholds for types `"probability"`, `"cumprob"`, and `"class"`. Can differ from thresholds used for fitting. If omitted, the same thresholds as for fitting are used.
`na.action`	A function which indicates what should happen when the data contain `NA`s. Default is na.pass
`...`	further arguments passed to or from other methods.

Value

For type "prob" a matrix with number of intervals (= number of thresholds + 1) columns is produced. Each row corresponds to a row in newdata and contains the predicted probabilities to fall in the corresponding interval.

For type "cumprob" a matrix with number of thresholds columns is produced. Each row corresponds to a row in newdata and contains the predicted probabilities to fall below the corresponding threshold.

For types "class", "location", and "scale" a vector is returned respectively with either the most probable categories ("class") or the location ("location") or scale (scale) of the latent distribution.