Simulation with Kernel Density Estimation

Generates random values from a univariate and multivariate continuous distribution by using kernel density estimation based on a sample. Duong (2017) , Christian P. Robert and George Casella (2010 ISBN:978-1-4419-1575-7) .


The R package for Simulation with Kernel Density Estimation

Features

  1. Generates random values from a univariate and multivariate continuous distribution by using kernel density estimation based on a sample.
  2. Finds the best fitting distribution from supported univariate continuous distributions for given data.

CRAN Page

https://cran.r-project.org/package=simukde

Example

## 1-dimensional data
data(faithful)
hist(faithful$eruptions)
res <- simukde::simulate_kde(x = faithful$eruptions, n = 1000)
hist(res$random.values)
 
## Simulation with the best fitting instrumental distribution
data(faithful)
par(mfrow = c(1, 3))
hist(faithful$eruptions)
fit <- simukde::find_best_fit(x = faithful$eruptions, positive = TRUE)
res <- simukde::simulate_kde(
  x = faithful$eruptions, n = 1000,
  distr = fit$distribution, parallel = FALSE
)
hist(res$random.values)
par(mfrow = c(1, 1))
 
## 2-dimensional data
data(faithful)
res <- simukde::simulate_kde(x = faithful, n = 100)
plot(res$kde, display = "filled.contour2")
points(x = res$random.values, cex = 0.25, pch = 16, col = "green")
points(x = faithful, cex = 0.25, pch = 16, col = "black")

Installation

From CRAN

install.packages("simukde")

From the repository on GitHub

install.packages("devtools")
devtools::install_github("galaamn/simukde")

Author

MAKHGAL Ganbold and BAYARBAATAR Amgalan, National University of Mongolia, 2018

Acknowledgment

Funding: This package has been done within the framework of the project Statistics and Optimization Based Methods for Identification of Cancer-Activated Biological Processes (P2017-2519) supported by the Asia Research Center, Mongolia and Korea Foundation for Advanced Studies, Korea.

The funders had no role in study design, analysis, decision to publish, or preparation of the package.

News

simukde 1.1.0

  • Added a NEWS.md file to track changes to the package.
  • The field ByteCompile was added into DESCRIPTION file with the value true.
  • Added input validations for the argument distr.
  • Supported more instrumental distributions hereto: Gamma, Cauchy, Log Normal, Weibull.
  • Imported the package MASS.
  • Added some tests for newly added instrumental distributions.
  • Added data validation for the chosen distribution by the argument distr.
  • Added the function find_best_fit for finding the best fitting instrumental univariate continuous distribution easily.
  • Suggested the package datasets.
  • Added an example for the function simulate_kde.
  • Added some tests for the new function find_best_fit.

Reference manual

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install.packages("simukde")

1.1.0 by MAKHGAL Ganbold, a year ago


https://github.com/galaamn/simukde


Report a bug at https://github.com/galaamn/simukde/issues


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


Authors: MAKHGAL Ganbold [aut, cre] , BAYARBAATAR Amgalan [aut]


Documentation:   PDF Manual  


GPL (>= 3) | file LICENSE license


Imports ks, mvtnorm, parallel, stats, MASS

Suggests testthat, datasets


See at CRAN