JAGS is a powerful tool in Bayesian statistics, but what if you want to model with a non-standard distribution or a distribution not supported in JAGS?
You’ve just created a package that will fit your model to any dataset the user supplies. How would the user view the model output and diagnostics?
In a previous post, knitr_tabset was introduced as a mean of programmatic tabsets. Can we improve this function using knit_print?
knitr_tabset
knit_print
In the previous post, I showed how the gghighlight package can allow the showing of many time series in the background whilst focusing on a handful of selected series. Can this idea be extended with interactivity?
gghighlight is a package that allows a user to focus on a key point within an otherwise messy visualisation. Will basic shiny functionality allow us to make this highlighting interactive?
Tabsets are a powerful tool available, in Quarto, that allows us to hide content into clearly separated sub-pages. Can we extend the Quarto syntax for tabs to work with an unknown number of elements?
Data arising from simulation studies are often chosen to best illustrate an author’s point. Here, we show how a dataset can be picked interactively using a small-scale Shiny application.
Using rjags in a quarto document lacks comforts such as a progress bar due to knitr complications. But can we leverage the power of R to workaround such an issue?
