Package index • posterior

Overview

Package overview and global options

posterior-package posterior: Tools for working with posterior (and prior) distributions

Draws objects and formats

Createdraws objects and convert between supported formats

as_draws() is_draws(): Transform to draws objects
as_draws_array() draws_array() is_draws_array(): The draws_array format
as_draws_df() draws_df() is_draws_df(): The draws_df format
as_draws_list() draws_list() is_draws_list(): The draws_list format
as_draws_matrix() draws_matrix() is_draws_matrix(): The draws_matrix format
as_draws_rvars() draws_rvars() is_draws_rvars(): The draws_rvars format
print(<draws_array>): Print draws_array objects
print(<draws_df>): Print draws_df objects
print(<draws_list>): Print draws_list objects
print(<draws_matrix>): Print draws_matrix objects
print(<draws_rvars>): Print draws_rvars objects
print(<draws_summary>): Print summaries of draws objects
print(<rvar>) format(<rvar>) str(<rvar>): Print or format a random variable
variables() nvariables(): Get variable names from draws objects
example_draws(): Example draws objects
reserved_variables(): Reserved variables

Working with draws objects

Functions for modifying draws objects and extracting their contents

bind_draws(): Bind draws objects together
extract_list_of_variable_arrays(): Extract arrays of multiple variables
extract_variable(): Extract draws of a single variable
extract_variable_array(): Extract array of a single (possibly indexed) variable
extract_variable_matrix(): Extract matrix of a single variable
merge_chains(): Merge chains of draws objects
mutate_variables(): Mutate variables in draws objects
`variables<-`() set_variables(): Set variable names in draws objects
order_draws(): Order draws objects
split_chains(): Split Chains
subset_draws() subset(<draws>): Subset draws objects
iteration_ids() chain_ids() draw_ids() niterations() nchains() ndraws(): Index draws objects
rename_variables(): Rename variables in draws objects
repair_draws(): Repair indices of draws objects
resample_draws(): Resample draws objects
thin_draws(): Thin draws objects
weight_draws(): Weight draws objects
weights(<draws>): Extract Weights from Draws Objects

Summarizing and diagnosing draws objects

Compute summary statistics and convergence diagnostics

summarise_draws() summarize_draws() summary(<draws>) summary(<rvar>) default_summary_measures() default_convergence_measures() default_mcse_measures(): Summaries of draws objects
diagnostics convergence: List of available convergence diagnostics
ess_basic(): Basic version of the effective sample size
ess_bulk(): Bulk effective sample size (bulk-ESS)
ess_mean(): Effective sample size for the mean
ess_quantile() ess_median(): Effective sample sizes for quantiles
ess_sd(): Effective sample size for the standard deviation
ess_tail(): Tail effective sample size (tail-ESS)
rhat(): Rhat convergence diagnostic
rhat_basic(): Basic version of the Rhat convergence diagnostic
rhat_nested(): Nested Rhat convergence diagnostic
mcse_mean(): Monte Carlo standard error for the mean
mcse_quantile() mcse_median(): Monte Carlo standard error for quantiles
mcse_sd(): Monte Carlo standard error for the standard deviation
pareto_diags() pareto_khat_threshold() pareto_min_ss() pareto_convergence_rate(): Pareto smoothing diagnostics
pareto_khat(): Pareto khat diagnostic
pareto_pit(): Pareto-smoothed probability integral transform
pareto_smooth(): Pareto smoothing
ps_convergence_rate(): Pareto convergence rate
ps_khat_threshold(): Pareto k-hat threshold
ps_min_ss(): Pareto-smoothing minimum sample-size
ps_tail(): Pareto smooth tail function to Pareto smooth the tail of a vector. Exported for usage in other packages, not by users.
ps_tail_length(): Pareto tail length
quantile2(): Compute Quantiles
rstar(): Calculate R* convergence diagnostic
entropy(): Normalized entropy
dissent(): Dissention
modal_category(): Modal category
pit(): Probability integral transform
uniformity_test(): Uniformity test for PIT values

Functionality specific to the rvar datatype

The draws_rvar format (a structured list of rvar objects) has the same methods (e.g. bind_draws()) as the other draws formats. For individual rvar objects themselves, however, posterior provides additional functionality.

chol(<rvar>): Cholesky decomposition of random matrix
density(<rvar>) density(<rvar_factor>) cdf(<rvar>) cdf(<rvar_factor>) cdf(<rvar_ordered>) quantile(<rvar>) quantile(<rvar_factor>) quantile(<rvar_ordered>): Density, CDF, and quantile functions of random variables
`%**%` matrixOps(<rvar>): Matrix multiplication of random variables
`[[`(<rvar>) `[[<-`(<rvar>) `[`(<rvar>) `[<-`(<rvar>): Random variable slicing
E() mean(<rvar>) Pr() median(<rvar>) min(<rvar>) max(<rvar>) sum(<rvar>) prod(<rvar>) all(<rvar>) any(<rvar>) Summary(<rvar>) variance(<rvar>) var() sd() mad() range(<rvar>) is.finite(<rvar>) is.infinite(<rvar>) is.nan(<rvar>) is.na(<rvar>): Summaries of random variables within array elements, over draws
rvar_mean() rvar_median() rvar_sum() rvar_prod() rvar_min() rvar_max() rvar_sd() rvar_var() rvar_mad() rvar_range() rvar_quantile() rvar_all() rvar_any(): Summaries of random variables over array elements, within draws
rvar(): Random variables of arbitrary dimension
rvar_apply(): Random variable resulting from a function applied over margins of an array or random variable
rvar_factor() rvar_ordered(): Factor random variables of arbitrary dimension
rvar_ifelse(): Random variable ifelse
rvar_is_finite() rvar_is_infinite() rvar_is_nan() rvar_is_na(): Special value predicates for random variables
rvar_rng(): Create random variables from existing random number generators
is_rvar(): Is x a random variable?
is_rvar_factor() is_rvar_ordered(): Is x a factor random variable?
as_rvar() as_rvar_numeric() as_rvar_integer() as_rvar_logical(): Coerce to a random variable
as_rvar_factor() as_rvar_ordered(): Coerce to a factor random variable
rdo(): Execute expressions of random variables
rfun(): Create functions of random variables
draws_of() `draws_of<-`(): Get/set array of draws underlying a random variable
diag(<rvar>): Matrix diagonals (including for random variables)
drop(<rvar>): Drop redundant dimensions
for_each_draw(): Loop over draws
match() `%in%`: Value Matching