Inference and Analysis for Generalized Quadratic Diffusions

Tools for performing inference and analysis on a class of quadratic diffusion processes for both scalar and bivariate diffusion systems. For scalar diffusions, a module is provided for solving first passage time problems for both time-homogeneous and time-inhomogeneous GQDs.


Inference and Analysis for Generalized Quadratic Diffusions

What is DiffusionRgqd?

DiffusionRgqd is collection of tools for performing inference and analysis on scalar and bivariate time-inhomogeneous diffusion processes with quadratic drift and diffusion terms in R.

Why use DiffusionRgqd?

DiffusionRgqd provides a simple interface that requires minimal mathematical input in order to perform analysis on non-linear, time-inhomogeneous diffusion processes. The package also makes use of C++ in order to maximize the computational efficiency of inference routines. As such it is possible to conduct inference on a plethora of models in a desktop environment without incurring excessively long computation times.

Get DiffusionRgqd?

Check out DiffusionRgqd for the package source files, vignettes and other downloadable content or visit the DiffusionRgqd CRAN page.

Installation Notes

Mac users may have to carry out some additional installation procedures in order for DiffusionRjgqd to operate optimally.

Mac users:

To install the latest version of Rcpp, the latest version of R is needed. To install RcppArmadillo, the Fortran version used by R needs to be updated. To install rgl, the computer needs to have X11 installed. Update R to the latest version. Run the following code: install.packages("Rcpp", type = "source",dep=T)

Open a Terminal and run the following code:

curl -O http://r.research.att.com/libs/gfortran-4.8.2-darwin13.tar.bz2 sudo tar fvxz gfortran-4.8.2-darwin13.tar.bz2 -C /

Back in R, run the following code:

install.packages("RcppArmadillo",dep=T)

Make sure you have X11 installed.

Go to Applications/Utilities and see if X11 is there. If not, you’ll need to install X11 or XQuartz. These are available from http://xquartz.macosforge.org/landing/

Back in R, run the following code:

install.packages(“rgl",dep=T) 

Download the DiffusionRjgqd package and run the code:

install.packages("~/DiffusionRgqd_0.1.3.tar.gz", repos = NULL, type = "source”)

Run the following code in R to see if the package works:

library(DiffpackRgqd) 
example(GQD.density)
example(GQD.mcmc)

News

DiffusionRgqd - NEWS

DiffusionRgqd is now available on CRAN and GitHub.

Check out DiffusionRgqd for the package source files, vignettes and other downloadable content or visit the DiffusionRgqd CRAN page.

v0.1.0

  • Initial version of DiffusionRgqd uploaded to CRAN and GitHub.

v0.1.1

  • Made minor example updates.

v0.1.2

  • Error checking updated.
  • Switch added for printing model info to the console.
  • Fixed missing characters in interface.
  • MCMC algorithm updating structure revised for stability.
  • Added detailed vignettes:
    • Introductory vignette
    • Generating transition densities
    • Solving first passage time problems
    • Performing inference on GQDs
  • Updated colour palettes for better human perception.
  • Improved root finding algorithm for bivariate saddlepoint approximations.

v0.1.3

  • Vignettes changed to html source.
  • Citation info updated

Reference manual

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install.packages("DiffusionRgqd")

0.1.3 by Etienne A.D. Pienaar, 2 years ago


https://github.com/eta21


Report a bug at https://github.com/eta21/DiffusionRgqd/issues


Browse source code at https://github.com/cran/DiffusionRgqd


Authors: Etienne A.D. Pienaar [aut, cre] , Melvin M. Varughese [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, RcppArmadillo, rgl, colorspace

Suggests knitr, coda, fptdApprox, Quandl, R.rsp

Linking to Rcpp, RcppArmadillo


Suggested by DiffusionRimp, DiffusionRjgqd.


See at CRAN