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posterior  

Tools for Working with Posterior Distributions
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("posterior", "1.6.1")



Attach the package and use:
library("posterior")
Maintained by
Paul-Christian Bürkner
[Scholar Profile | Author Map]
First Published: 2021-07-13
Latest Update: 2023-10-31
Description:
Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) .
How to cite:
Paul-Christian Bürkner (2021). posterior: Tools for Working with Posterior Distributions. R package version 1.6.1, https://cran.r-project.org/web/packages/posterior. Accessed 10 Apr. 2025.
Previous versions and publish date:
1.0.0 (2021-07-13 17:40), 1.0.1 (2021-07-14 14:30), 1.1.0 (2021-09-09 13:30), 1.2.0 (2022-01-05 17:50), 1.2.1 (2022-03-07 13:40), 1.2.2 (2022-06-10 01:00), 1.3.0 (2022-08-15 15:40), 1.3.1 (2022-09-06 16:10), 1.4.0 (2023-02-22 23:40), 1.4.1 (2023-03-14 10:10), 1.5.0 (2023-10-31 09:30), 1.6.0 (2024-07-04 01:00)
Other packages that cited posterior R package
View posterior citation profile
Other R packages that posterior depends, imports, suggests or enhances
Complete documentation for posterior
Functions, R codes and Examples using the posterior R package
Some associated functions: as_rvar . as_rvar_factor . autocorrelation . autocovariance . bind_draws . chol.rvar . diag-rvar-method . diagnostics . dissent . draws-index . draws . draws_array . draws_df . draws_list . draws_matrix . draws_of . draws_rvars . draws_summary . drop-rvar-method . entropy . ess_basic . ess_bulk . ess_mean . ess_quantile . ess_sd . ess_tail . example_draws . extract_variable . extract_variable_matrix . for_each_draw . is_rvar . is_rvar_factor . match . mcse_mean . mcse_quantile . mcse_sd . merge_chains . modal_category . mutate_variables . order_draws . pareto_diags . pareto_khat . pareto_smooth . posterior-package . print.draws_array . print.draws_df . print.draws_list . print.draws_matrix . print.draws_rvars . print.draws_summary . print.rvar . quantile2 . r_scale . rdo . reexports . rename_variables . repair_draws . resample_draws . reserved_variables . rfun . rhat . rhat_basic . rhat_nested . rstar . rvar-dist . rvar-matmult . rvar-slice . rvar-summaries-over-draws . rvar-summaries-within-draws . rvar . rvar_apply . rvar_factor . rvar_ifelse . rvar_is_finite . rvar_rng . set_variables . split_chains . sub-.draws_array . sub-.draws_matrix . subset_draws . thin_draws . u_scale . weight_draws . weights.draws . z_scale . 
Some associated R codes: as_draws.R . as_draws_array.R . as_draws_df.R . as_draws_list.R . as_draws_matrix.R . as_draws_rvars.R . bind_draws.R . convergence.R . discrete-summaries.R . draws-index.R . example_draws.R . extract_variable.R . extract_variable_matrix.R . for_each_draw.R . gpd.R . merge_chains.R . misc.R . mutate_variables.R . nested_rhat.R . order_draws.R . pareto_smooth.R . posterior-package.R . print.R . remove_variables.R . rename_variables.R . repair_draws.R . resample_draws.R . reserved_variables.R . rstar.R . rvar-.R . rvar-apply.R . rvar-bind.R . rvar-cast.R . rvar-dim.R . rvar-dist.R . rvar-factor.R . rvar-math.R . rvar-print.R . rvar-rfun.R . rvar-slice.R . rvar-summaries-over-draws.R . rvar-summaries-within-draws.R . split_chains.R . subset_draws.R . summarise_draws.R . thin_draws.R . weight_draws.R . zzz.R .  Full posterior package functions and examples
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