Predict method for clmstan objects

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.