Other packages > Find by keyword >

parallelMCMCcombine  

Combining Subset MCMC Samples to Estimate a Posterior Density
View on CRAN: Click here


Download and install parallelMCMCcombine package within the R console
Install from CRAN:
install.packages("parallelMCMCcombine")

Install from Github:
library("remotes")
install_github("cran/parallelMCMCcombine")

Install by package version:
library("remotes")
install_version("parallelMCMCcombine", "2.0")



Attach the package and use:
library("parallelMCMCcombine")
Maintained by
Erin Conlon
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-06-20
Latest Update: 2021-06-23
Description:
See Miroshnikov and Conlon (2014) . Recent Bayesian Markov chain Monto Carlo (MCMC) methods have been developed for big data sets that are too large to be analyzed using traditional statistical methods. These methods partition the data into non-overlapping subsets, and perform parallel independent Bayesian MCMC analyses on the data subsets, creating independent subposterior samples for each data subset. These independent subposterior samples are combined through four functions in this package, including averaging across subset samples, weighted averaging across subsets samples, and kernel smoothing across subset samples. The four functions assume the user has previously run the Bayesian analysis and has produced the independent subposterior samples outside of the package; the functions use as input the array of subposterior samples. The methods have been demonstrated to be useful for Bayesian MCMC models including Bayesian logistic regression, Bayesian Gaussian mixture models and Bayesian hierarchical Poisson-Gamma models. The methods are appropriate for Bayesian hierarchical models with hyperparameters, as long as data values in a single level of the hierarchy are not split into subsets.
How to cite:
Erin Conlon (2014). parallelMCMCcombine: Combining Subset MCMC Samples to Estimate a Posterior Density. R package version 2.0, https://cran.r-project.org/web/packages/parallelMCMCcombine. Accessed 26 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:39), 1.0 (2014-06-20 08:03)
Other packages that cited parallelMCMCcombine R package
View parallelMCMCcombine citation profile
Other R packages that parallelMCMCcombine depends, imports, suggests or enhances
Complete documentation for parallelMCMCcombine
Functions, R codes and Examples using the parallelMCMCcombine R package
Some associated functions: consensusMCcov . consensusMCindep . parallelMCMCcombine-package . sampleAvg . semiparamDPE . 
Some associated R codes: consensusMCcov.R . consensusMCindep.R . sampleAvg.R . semiparamDPE.R .  Full parallelMCMCcombine package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

SelvarMix  
Regularization for Variable Selection in Model-Based Clustering and Discriminant Analysis
Performs a regularization approach to variable selection in themodel-based clustering and classifica ...
Download / Learn more Package Citations See dependency  
leafgl  
High-Performance 'WebGl' Rendering for Package 'leaflet'
Provides bindings to the 'Leaflet.glify' JavaScript library which extends the 'leaflet' JavaScript l ...
Download / Learn more Package Citations See dependency  
RCytoGPS  
Using Cytogenetics Data in R
Defines classes and methods to process text-based cytogenetics using the CytoGPS web site, then imp ...
Download / Learn more Package Citations See dependency  
ncodeR  
Techniques for Automated Classifiers
A set of techniques that can be used to develop, validate, and implement automated classifiers. A po ...
Download / Learn more Package Citations See dependency  
PCADSC  
Tools for Principal Component Analysis-Based Data Structure Comparisons
A suite of non-parametric, visual tools for assessing differences in data structures for two datase ...
Download / Learn more Package Citations See dependency  
clinUtils  
General Utility Functions for Analysis of Clinical Data
Utility functions to facilitate the import, the reporting and analysis of clinical data. Example ...
Download / Learn more Package Citations See dependency  

28,332

R Packages

239,283

Dependencies

75,113

Author Associations

28,333

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA