bayestestR | :ghost: Utilities for analyzing Bayesian models and posterior distributions | Development Tools library
kandi X-RAY | bayestestR Summary
kandi X-RAY | bayestestR Summary
:warning: We changed the default the CI width! Please make an informed decision and set it explicitly (ci = 0.89, ci = 0.95 or anything else that you decide) :warning:. Existing R packages allow users to easily fit a large variety of models and extract and visualize the posterior draws. However, most of these packages only return a limited set of indices (e.g., point-estimates and CIs). bayestestR provides a comprehensive and consistent set of functions to analyze and describe posterior distributions generated by a variety of models objects, including popular modeling packages such as rstanarm, brms or BayesFactor.
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Trending Discussions on bayestestR
QUESTION
How can I determine the confidence/credibility intervals for the posterior estimates of a multi-parameter model?
I can get the confidence interval for each parameter separately.
(Currently using bayestestR
, but I don't mind using something else)
ANSWER
Answered 2022-Jan-03 at 17:42Here's one base-R-plotting solution, which plots a 95% highest posterior density region based on a 2-D kernel density estimate:
QUESTION
I have followed the code on this solution to plot multiple regressions using dot-and-whiskers, but receive the following error when trying to replicate results and when running the code with my own data and models:
...ANSWER
Answered 2021-Oct-17 at 19:24I found a solution to my own question using tidy models
, as suggested here.
QUESTION
I would like to perform Bayesian Logistic Regression using the bayestestR
and rstanarm
in R. The output, I believe, is in the log(odds ratio). Do you know of a way in which I can convert everything, i.e. the centrality, uncertainty, existence and significance indices into odds ratio instead. I know tbl_summary
function from gtsummary
package has an argument, exponentiate = TRUE
that returns everything in OR.
Code:
...ANSWER
Answered 2021-Jun-29 at 12:23I'd recommend using the parameters
package which uses bayestestR internally but is more flexible:
QUESTION
I am trying to plot a density line with and want to shade or fill only the area associated with the 95% of the x axis. I am trying to follow answers given in the attached answers, but non of them talk about shading an area when we are plotting more than one distributions at the same time with a grouping factor. In this case the grouping factor is the different central electrodes ("Fz", "Cz, "Pz"). I am trying to visualise something similar to the highest density interval, or the area under the curve comprising between percentile 5 and 95.
My data looks something like this:
...ANSWER
Answered 2020-Oct-07 at 16:20Since you need to do some maths on the density curves to work out where the 95% intervals are, it is best to do this outside ggplot. I often find that people run into problems because they try to get ggplot to do too much of their data wrangling and summarizing. It is often easier to work out what you want to plot, then plot it.
In your case, your x and y co-ordinates already represent densities. For each Electrode, you just need to create a logical vector that tells you when the integral of the density is between 0.025 and 0.975, so that you can easily subset out the 95% confidence interval. You can do that using the split-aplly-bind method like this:
QUESTION
I have a dataset like this:
...ANSWER
Answered 2020-Sep-02 at 20:48It becomes clearer when you do not assign your first line of code:
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