vctrs_methods_posterior: Extra methods for the posterior class to work with dplyr...

In tidyposterior: Bayesian Analysis to Compare Models using Resampling Statistics

Extra methods for the posterior class to work with dplyr verbs

Description

Objects with class posterior are defined to be tibbles with required columns model (character) and posterior (numeric). If operations on these objects break those rules, they are down-cast to basic tibbles.

Usage

vec_restore.posterior(x, to, ...)

vec_proxy.posterior(x, ...)

vec_ptype2.posterior.posterior(x, y, ..., x_arg = "", y_arg = "")

vec_ptype2.posterior.tbl_df(x, y, ..., x_arg = "", y_arg = "")

vec_ptype2.tbl_df.posterior(x, y, ..., x_arg = "", y_arg = "")

vec_ptype2.posterior.data.frame(x, y, ..., x_arg = "", y_arg = "")

vec_ptype2.data.frame.posterior(x, y, ..., x_arg = "", y_arg = "")

vec_cast.posterior.posterior(x, to, ..., x_arg = "", to_arg = "")

vec_cast.posterior.tbl_df(x, to, ..., x_arg = "", to_arg = "")

vec_cast.tbl_df.posterior(x, to, ..., x_arg = "", to_arg = "")

vec_cast.posterior.data.frame(x, to, ..., x_arg = "", to_arg = "")

vec_cast.data.frame.posterior(x, to, ..., x_arg = "", to_arg = "")

tidyposterior documentation built on Oct. 12, 2023, 1:07 a.m.