predict.clmstan: Predict method for clmstan objects

In clmstan: Cumulative Link Models with 'CmdStanR'

Predict method for clmstan objects

Description

Generates predictions from a fitted cumulative link model.

Usage

## S3 method for class 'clmstan'
predict(
  object,
  newdata = NULL,
  type = c("class", "probs"),
  summary = TRUE,
  robust = FALSE,
  probs = c(0.025, 0.975),
  ndraws = NULL,
  ...
)

Arguments

object	A clmstan object returned by clm_stan().
newdata	Optional data frame for prediction. If NULL (default), predictions are made for the original training data.
type	Type of prediction: "class": Predicted category (most likely class) "probs": Predicted probabilities for each category
summary	Logical. If TRUE (default), return summary statistics (mean, SD, quantiles). If FALSE, return raw posterior draws.
robust	Logical. If TRUE, use median instead of mean for point estimates. Default is FALSE.
probs	Numeric vector of probabilities for quantiles. Default is c(0.025, 0.975) for 95% credible intervals.
ndraws	Number of posterior draws to use. If NULL (default), all available draws are used.
...	Additional arguments (currently ignored).

Value

Depending on type and summary:

• type = "class", summary = TRUE: A data frame with columns Estimate (mean/median predicted class), Est.Error (SD), quantile columns, and Class (modal predicted category).

• type = "class", summary = FALSE: An S x N integer matrix of predicted categories (1 to K), where S is the number of posterior draws and N is the number of observations.

• type = "probs", summary = TRUE: A data frame with columns for each category probability (P[Y=1], P[Y=2], etc.).

• type = "probs", summary = FALSE: An S x N x K array of predicted probabilities.

See Also

fitted.clmstan() for expected probabilities, posterior_predict.clmstan() for posterior predictive samples.

clmstan documentation built on June 29, 2026, 5:06 p.m.