vinecop_predict_and_fitted  R Documentation 
Predictions of the density and distribution function for a vine copula model.
## S3 method for class 'vinecop' predict(object, newdata, what = "pdf", n_mc = 10^4, cores = 1, ...) ## S3 method for class 'vinecop' fitted(object, what = "pdf", n_mc = 10^4, cores = 1, ...)
object 
a 
newdata 
points where the fit shall be evaluated. 
what 
what to predict, either 
n_mc 
number of samples used for quasi Monte Carlo integration when

cores 
number of cores to use; if larger than one, computations are
done in parallel on 
... 
unused. 
fitted()
can only be called if the model was fit with the
keep_data = TRUE
option.
When at least one variable is discrete, two types of
"observations" are required in newdata
: the first n \; x \; d block
contains realizations of F_{X_j}(X_j). The second n \; x \; d
block contains realizations of F_{X_j}(X_j^). The minus indicates a
leftsided limit of the cdf. For, e.g., an integervalued variable, it holds
F_{X_j}(X_j^) = F_{X_j}(X_j  1). For continuous variables the left
limit and the cdf itself coincide. Respective columns can be omitted in the
second block.
fitted()
and predict()
have return values similar to dvinecop()
and pvinecop()
.
u < sapply(1:5, function(i) runif(50)) fit < vinecop(u, family = "par", keep_data = TRUE) all.equal(predict(fit, u), fitted(fit), check.environment = FALSE)
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