In ShashankKumbhare/paramonteR: Plain Powerful Parallel Monte Carlo Library

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

paramonte

ParaMonte is a serial / parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference.

Installation

You can install the released version of paramonte from CRAN with:

install.packages("paramonte")

Example

This is a basic example which shows you how to solve a common problem:

library(paramonte)
## basic example code

What is special about using README.Rmd instead of just README.md? You can include R chunks like so:

summary(cars)

You'll still need to render README.Rmd regularly, to keep README.md up-to-date. devtools::build_readme() is handy for this. You could also use GitHub Actions to re-render README.Rmd every time you push. An example workflow can be found here: https://github.com/r-lib/actions/tree/master/examples.

You can also embed plots, for example:

plot(pressure)

In that case, don't forget to commit and push the resulting figure files, so they display on GitHub and CRAN.

ShashankKumbhare/paramonteR documentation built on April 25, 2022, 12:08 a.m.