continuous_continuous_loglik: Loglikelihood function for continuous-continuous copula model

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Loglikelihood function for continuous-continuous copula model

Description

continuous_continuous_loglik() computes the observed-data loglikelihood for a bivariate copula model with two continuous endpoints.

Usage

continuous_continuous_loglik(
  para,
  X,
  Y,
  copula_family,
  marginal_X,
  marginal_Y,
  return_sum = TRUE
)

Arguments

para	Parameter vector. The parameters are ordered as follows: para[1:p1]: Parameters for the distribution of X as specified in marginal_X. para[(p1 + 1):(p1 + p2)]: Parameters for the distribution of Y as specified in marginal_Y. para[p1 + p2 + 1]: copula parameter
X	First variable (Continuous)
Y	Second variable (Continuous)
copula_family	Copula family, one of the following: "clayton" "frank" "gumbel" "gaussian"
marginal_X, marginal_Y	List with the following three elements (in order): Density function with first argument x and second argument para the parameter vector for this distribution. Distribution function with first argument x and second argument para the parameter vector for this distribution. Inverse distribution function with first argument p and second argument para the parameter vector for this distribution. The number of elements in para. A vector of starting values for para.
return_sum	Return the sum of the individual loglikelihoods? If FALSE, a vector with the individual loglikelihood contributions is returned.

Value

(numeric) loglikelihood value evaluated in para.

Surrogate documentation built on April 11, 2025, 6:09 p.m.