Make Prediction on New Data (Advanced) — htlr

This function uses MCMC samples from fitted htlrfit object OR user supplied regression coefficient to predict the class labels of test cases.

Usage

htlr_predict(
  X_ts,
  fithtlr = NULL,
  deltas = NULL,
  burn = NULL,
  thin = 1,
  usedmc = NULL,
  rep.legacy = TRUE
)

X_ts: Matrix of values at which predictions are to be made.
fithtlr: Fitted HTLR model object.
deltas: The values of deltas (for example true deltas) used to make prediction; will override fithtlr if provided.
burn, thin: burn of Markov chain (super)iterations will be discarded for prediction, and only every thin are used.
usedmc: Indices of Markov chain iterations used for inference. If supplied, burn and thin will be ignored.
rep.legacy: To reproduce (actually incorrect) results in legacy version. See https://github.com/longhaiSK/HTLR/issues/7.

A matrix of predictive probabilities, with rows for cases, cols for classes.