README

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Rtwalk: An MCMC Sampler Using the t-walk Algorithm

Rtwalk is an R implementation of the t-walk, a general-purpose Markov Chain Monte Carlo (MCMC) sampler for continuous distributions, ideal for Bayesian inference problems.

Overview

This package provides a implementation of the t-walk algorithm, as originally proposed by Christen & Fox (2010). The t-walk is a robust, self-adjusting MCMC sampler, which means it does not require the tedious manual tuning of proposal parameters. It is designed to efficiently explore a wide range of target distributions, maintaining good performance even in high-dimensional or multimodal problems.

Installation

You can install the development version of Rtwalk from GitHub using the devtools package:

# If you don't have the devtools package, install it first
# install.packages("devtools")

devtools::install_github("rodrigosqrt3/Rtwalk", build_vignettes = TRUE)

Example Usage

Here is a simple example of how to use Rtwalk to sample from a bimodal distribution.

library(Rtwalk)

# Define the log-posterior density of the target distribution
# In this case, a mixture of two normal distributions
log_posterior_bimodal <- function(x) {
  log(0.5 * dnorm(x, mean = -3, sd = 0.5) + 0.5 * dnorm(x, mean = 3, sd = 0.5))
}

initial_point_1 <- -3
initial_point_2 <- 3

result <- twalk(
  log_posterior = log_posterior_bimodal,
  n_iter = 50000,
  x0 = initial_point_1,
  xp0 = initial_point_2
)

burnin <- nrow(result$all_samples) * 0.2
samples <- result$all_samples[-(1:burnin), ]

par(mfrow = c(1, 2))
hist(samples, breaks = 50, freq = FALSE, 
     main = "Posterior Distribution", xlab = "Parameter Value")
lines(density(samples), col = "blue", lwd = 2)

plot(samples, type = 'l', col = "grey30", 
     main = "Trace Plot", xlab = "Iteration")

Citation

This package is an implementation of the algorithm described in the following paper. If you use Rtwalk in your research, please cite the original work:

License

This package is licensed under the GPL-3. See the LICENSE file for more details.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.