https://github.com/cran/bayestestR
Revision 9985109256c08d654edb46adb9cb20c913fb1888 authored by Dominique Makowski on 29 May 2019, 14:10:02 UTC, committed by cran-robot on 29 May 2019, 14:10:02 UTC
1 parent fe07bfa
Tip revision: 9985109256c08d654edb46adb9cb20c913fb1888 authored by Dominique Makowski on 29 May 2019, 14:10:02 UTC
version 0.2.0
version 0.2.0
Tip revision: 9985109
credible_interval.R
## ----message=FALSE, warning=FALSE, include=FALSE-------------------------
library(knitr)
options(knitr.kable.NA = '')
knitr::opts_chunk$set(comment=">")
options(digits=2)
set.seed(333)
## ----warning=FALSE, message=FALSE----------------------------------------
library(bayestestR)
library(dplyr)
library(ggplot2)
# Generate a normal distribution
posterior <- distribution_normal(1000)
# Compute HDI and Quantile CI
ci_hdi <- hdi(posterior)
ci_eti <- ci(posterior)
# Plot the distribution and add the limits of the two CIs
posterior %>%
estimate_density(extend=TRUE) %>%
ggplot(aes(x=x, y=y)) +
geom_area(fill="orange") +
theme_classic() +
# HDI in blue
geom_vline(xintercept=ci_hdi$CI_low, color="royalblue", size=3) +
geom_vline(xintercept=ci_hdi$CI_high, color="royalblue", size=3) +
# Quantile in red
geom_vline(xintercept=ci_eti$CI_low, color="red", size=1) +
geom_vline(xintercept=ci_eti$CI_high, color="red", size=1)
## ----warning=FALSE, message=FALSE----------------------------------------
library(bayestestR)
library(dplyr)
library(ggplot2)
# Generate a beta distribution
posterior <- distribution_beta(1000, 6, 2)
# Compute HDI and Quantile CI
ci_hdi <- hdi(posterior)
ci_eti <- ci(posterior)
# Plot the distribution and add the limits of the two CIs
posterior %>%
estimate_density(extend=TRUE) %>%
ggplot(aes(x=x, y=y)) +
geom_area(fill="orange") +
theme_classic() +
# HDI in blue
geom_vline(xintercept=ci_hdi$CI_low, color="royalblue", size=3) +
geom_vline(xintercept=ci_hdi$CI_high, color="royalblue", size=3) +
# Quantile in red
geom_vline(xintercept=ci_eti$CI_low, color="red", size=1) +
geom_vline(xintercept=ci_eti$CI_high, color="red", size=1)
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