mcmcse: Monte Carlo Standard Errors for MCMC

Canonical link: https://scholar.rpkg.net/pkg/mcmcse

James M. Flegal, • John Hughes, • Dootika Vats, • Ning Dai, • Kushagra Gupta, and • Uttiya Maji • View description and downloads View dependencies GitHub project

2012 Published

1.5-0 Version

0 Citations

6 Authors

Referenced by ⇅	Year
eiCompare: Compares Different Ecological Inference Methods (Version 3.0.4)	2016
DSSP: Implementation of the Direct Sampling Spatial Prior (Version 0.1.1)	2022
JointAI: Joint Analysis and Imputation of Incomplete Data (Version 1.0.6)	2018
LNIRT: LogNormal Response Time Item Response Theory Models (Version 0.5.1)	2016
bayes4psy: User Friendly Bayesian Data Analysis for Psychology (Version 1.2.12)	2019
bayesImageS: Bayesian Methods for Image Segmentation using a Potts Model (Version 0.6-1)	2016
bpgmm: Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models (Version 1.0.9)	2019
copCAR: Fitting the copCAR Regression Model for Discrete Areal Data (Version 2.0-4)	2015
dirmcmc: Directional Metropolis Hastings Algorithm (Version 1.3.3)	2017
genMCMCDiag: Generalized Convergence Diagnostics for Difficult MCMC Algorithms (Version 0.2.1)	2024
nimble: MCMC, Particle Filtering, and Programmable Hierarchical Modeling (Version 1.2.0)	2016
nse: Numerical Standard Errors Computation in R (Version 1.21)	2017
postpack: Utilities for Processing Posterior Samples Stored in 'mcmc.lists' (Version 0.5.4)	2020
qbld: Quantile Regression for Binary Longitudinal Data (Version 1.0.3)	2020
remiod: Reference-Based Multiple Imputation for Ordinal/Binary Response (Version 1.0.2)	2022
sklarsomega: Measuring Agreement Using Sklar's Omega Coefficient (Version 3.0-2)	2018
stableGR: A Stable Gelman-Rubin Diagnostic for Markov Chain Monte Carlo (Version 1.2)	2020

RPKG Scholar presents a tabulation of an author's contribution in the development of R packages stored in the Comprehensive R Archive Network (CRAN). Within this site, we consider package dependencies (suggests,imports,depends,enhances) as citations because we believe that using one's package to develop another is tantamount to citing the author of the package being imported, suggested or enhanced.