cmc: Fit a CMC model
In vincenzocoia/cmc: Copula-Marginal Composition Method

Intended to be used after a marginal model has been fit with composite_dist(). So, the actual fitting that's done here is strictly copula fitting, but the output is the entire model. Limited capability here – two predictors are assumed to be lags, and therefore having the same marginals.

cmc(ycol, x1col, x2col, data, method = "optim", force_ig = TRUE,
  marginal = NULL, sc, verbose = FALSE, copspace = NULL,
  families = c("indepcop", "bvncop", "bvtcop", "mtcj", "gum", "frk",
  "joe", "bb1", "bskewncop", "bskewncopp"))

`ycol, x1col, x2col`	Character names of the columns.
`data`	Data frame of data
`method`	Method of fitting. For MLE (the default), one of "optim" or "nlm", depending on the numerical optimizer you want to use. If "cnqr", fits by CNQR, and you need to specify the sc argument.
`force_ig`	Force Y and X1 to have dependence described by an IG copula? Default is TRUE.
`marginal`	Marginal model, assumed to be the same for the response and predictors. If NULL, assumes variables are already PIT scores; otherwise, really is expecting the output from the composite_dist() function.
`sc`	Scorer obtained through scorer()
`verbose`	Only works for CNQR. If TRUE, will output the fitting status of CNQR.
`copspace`	Only works for CNQR.
`families`	Vector of copula family names acting as a "pool" to choose from when fitting.