predict_class_posterior: predict_class_posterior

In sparktseung/LRMoE: Logit-Weighted Reduced Mixture-of-Experts

predict_class_posterior

Description

: Predicts the latent class probabilities, given observations Y, covariates X, logit regression coefficients alpha and a specified model of expert functions.

Usage

predict_class_posterior(
  Y,
  X,
  alpha,
  model,
  exposure_past = list(),
  exact_Y = F
)

Arguments

Y	A matrix of responses.
X	A matrix of covariates.
alpha	A matrix of logit regression coefficients.
model	A matrix specifying the expert functions.
exposure_past	A vector indicating the time exposure (past) of each observation. If nothing is supplied, it is set to 1.0 by default.
exact_Y	true or false (default), indicating if Y is observed exactly or with censoring and truncation.

Value

prob: A matrix of latent class probabilities.

max_prob_idx: A matrix of the most likely latent class for each observation.

sparktseung/LRMoE documentation built on March 21, 2022, 3:22 a.m.