A direct approach to optimal designs for copula models based on the
Fisher information. Provides flexible functions for building joint PDFs,
evaluating the Fisher information and finding optimal designs. It
includes an extensible solution to summation and integration called
nint
, functions for transforming, plotting and comparing
designs, as well as a set of tools for common low-level tasks.
docopulae strives to provide functions which allow the user to * define a wide variety of models by the joint probability density function (PDF) * evaluate the Fisher information by providing a convenient interface * find optimal designs using some sensitivity function * visualize designs * compare Ds-optimal designs
See ./misc/workflow.dot.pdf and ./misc/nint.dot.pdf. Vignettes explaining these steps in detail are planned.
First of all, if you are completely unfamiliar with R then I strongly recommend you to read “A (very) short introduction to R” first (just google it). Basic knowledge is necessary and assumed almost everywhere.
TODO. For the moment see and follow the example for the function
param
on the corresponding help page. It requires at least
the packages copula
, SparseGrid
and
numDeriv
to be installed. Run
devtools::update_packages(c('copula', 'SparseGrid', 'numDeriv'))
(or instead with install.packages
) to install/update them.
To install/update all suggested packages run
devtools::update_packages(c('copula', 'numDeriv', 'Deriv', 'cubature', 'SparseGrid', 'mvtnorm', 'testthat'))
.
If R’s help won’t work after installing the packages, restart R to resolve.
Have fun :)
install.packages('docopulae')
devtools::install_github('arappold/docopulae')
install.packages('/path/to/docopulae-master', repos=NULL, type='source')
If you are absolutely certain that you found a bug, please let me know by creating an issue at https://github.com/arappold/docopulae/issues. Explain how to reproduce the bug, best by attaching a small script, and I will investigate as soon as I got time to.
(just a) Warning: docopulae allows complex/complicated scripts. And even though we might think we know what it tells R what to do, we most often don’t.
If you feel unhappy about certain aspects of docopulae and perhaps have an adequate solution, please create an issue and lets discuss about it.