predict_VaRCTE_posterior: predict_VaRCTE_posterior

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

predict_VaRCTE_posterior

Description

Predicts the p-th value-at-risk (VaR) and conditional tail expectation (CTE) of response, given observations Y, covariates X, logit regression coefficients alpha and a specified model of expert functions.

Usage

predict_VaRCTE_posterior(
  Y,
  X,
  alpha,
  model,
  p,
  exposure_past = list(),
  exposure_future = 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.
p	A matrix of probabilities.
exposure_past	A vector indicating the time exposure (past) of each observation. If nothing is supplied,it is set to 1.0 by default.
exposure_future	A vector indicating the time exposure (future) of each observation. If nothing is supplied,it is set to 1.0 by default.
exact_Y	Bool variable. indicating if Y is observed exactly or with censoring and truncation. Default set to be False

Value

result: list(VaR, CTE) VaR: A matrix of predicted VaR of response, based on posterior probabilities. CTE: A matrix of predicted CTE of response, based on posterior probabilities.

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