fit_copula_submodel_OrdOrd: Fit ordinal-continuous copula submodel

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

Fit ordinal-continuous copula submodel

Description

The fit_copula_submodel_OrdOrd() function fits the copula (sub)model for an ordinal surrogate and true endpoint with maximum likelihood.

Usage

fit_copula_submodel_OrdOrd(
  X,
  Y,
  copula_family,
  start_copula,
  method = "BFGS",
  K_X,
  K_Y,
  names_XY = c("Surr", "True"),
  twostep = FALSE,
  ...
)

Arguments

X	First variable (Ordinal with K_X categories)
Y	Second variable (Ordinal with K_Y categories)
copula_family	Copula family, one of the following: "clayton" "frank" "gumbel" "gaussian"
start_copula	Starting value for the copula parameter.
method	Optimization algorithm for maximizing the objective function. For all options, see ?maxLik::maxLik. Defaults to "BFGS".
K_X	Number of categories in X.
K_Y	Number of categories in Y.
names_XY	Names for X and Y, respectively.
twostep	(boolean) If TRUE, the starting values are fixed for the marginal distributions and only the copula parameter is estimated.
...	Extra argument to pass onto maxLik::maxLik

Value

A list with five elements:

• ml_fit: object of class maxLik::maxLik that contains the estimated copula model.

• marginal_X: list with the estimated cdf, pdf/pmf, and inverse cdf for X.

• marginal_Y: list with the estimated cdf, pdf/pmf, and inverse cdf for X.

• copula_family: string that indicates the copula family

• data: data frame containing X and Y

• names_XY: The names (i.e., "Surr" and "True") for X and Y

Surrogate documentation built on June 8, 2025, 1:09 p.m.