evd-internal {evd} | R Documentation

## Internal Functions

### Description

The evd package contains many internal functions that are not designed to be called by the user.

The generic functions `dens`, `pp`, `qq` and `rl` create the diagnostic plots generated by `plot.uvevd`. Similarly, `bvdens`, `bvcpp` and `bvdp` create the diagnostic plots generated by `plot.bvevd`.

There are internal fitting, simulation, distribution and density functions for each bivariate and multivariate parametric model, which are called from functions such as `rbvevd` and `rmvevd`. There also exists internal functions for the calculation and plotting of dependence functions of bivariate and trivariate models, which are called from `abvdep` and `atvdep`. The dependence functions are ultimately plotted by the low-level functions `bvdepfn` and `tvdepfn`.

The function `pcint` calculates profile confidence intervals, and is called from the function `plot.profile.evd`. The fitting function `fgev` calls the internal functions `fgev.quantile` and `fgev.norm` for fits under different parameterizations. The fitting function `fpot` calls the internal functions `fpot.norm` and `fpot.quantile`. Marginal transformations are executed using `mtransform`.

The function `ccop` calculates condition copulas (i.e. conditional distributions under uniform margins) for each bivariate parametric model. This is needed to create the conditional P-P plots generated by `bvcpp`.

The functions `nsloc.transform`, `na.vals`, `bvpost.optim`, `bvstart.vals` and `sep.bvdata` are used in the fitting of bivariate models. The function `mvalog.check` checks and transforms the `asy` argument for the multivariate asymmetric model.

For fitting bivariate threshold models, internal functions exist for the censored and (currently unimplemented) point process likelihoods, and each of these calls a further internal function corresponding to the specified model. The internal function `bvtpost.optim` is then used for post optimization processing.

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