The fit_copula_submodel_OrdCont() function fits the copula (sub)model for a
continuous surrogate and an ordinal true endpoint with maximum likelihood.
fit_copula_submodel_OrdCont(
X,
Y,
copula_family,
marginal_Y,
start_Y,
start_copula,
method = "BFGS",
K,
names_XY = c("Surr", "True"),
twostep = FALSE,
...
)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
First variable (Ordinal with \(K\) categories)
Second variable (Continuous)
Copula family, one of the following:
"clayton"
"frank"
"gumbel"
"gaussian"
List with the following five 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.
Inverse distribution function with first argument p and second argument para.
The number of elements in para.
Starting values for para.
Starting values for the marginal distribution paramters for Y.
Starting value for the copula parameter.
Optimization algorithm for maximizing the objective function.
For all options, see ?maxLik::maxLik. Defaults to "BFGS".
Number of categories in X.
Names for X and Y, respectively.
(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
ordinal_continuous_loglik()