R-bloggers

Shiny in Production is heading back to The Catalyst in Newcastle upon Tyne this October! We’ve got a great mix of workshops and a full day of talks, with speakers being announced soon. You’ll find all the workshop details below, and you can sign up now on the ...

Introduction The Dyn4cast function was launched purposely to facilitate fast and easy forecast of COVID-19 cases in Nigeria. It was converted to a package and the development version of the package was launched on the 17th of February, 2021 with a si...

A researcher recently approached me for advice on a cluster-randomized trial he is developing. He is interested in testing the effectiveness of two interventions and wondered whether a 2×2 factorial design might be the best approach. As we discussed...

In a previous post, we presented an rjags version of a Bayesian model from Chapter 2 of the textbook: Evidence Synthesis for Decision Making in Healthcare by Welton et al. (2012). In this post, we continue our project to present rjags versi...

I’ve been busy with the field exams, so I haven’t had much time to work on the blog. spuriouscorrelations package started as a fun project for one of my tutorials. Here is a case of an interesting correlation: the number of people who drowned by ...

Refreshed my rusty calculus skills lately! 🤓 Finally understand what happens during complete separation and why those coefficient SE get so extreme. The math behind maximum likelihood estimation makes more sense now! Chain rule, quotient rule, matrix ...

tl;dr Once the login package is installed, you can run two demos using the following commands: shiny::runApp(paste0(find.package('login'), '/user_params/')) https://github.com/jbryer/login/blob/main/inst/user_params/app.R shiny::runApp(paste0(fi...

There are a bunch of new features to share as part of the 0.6.0 release of maestro: maestroFlags tag and accompanying get_flags() function for tagging pipelines. maestroPriority tag for determining the order in which simultaneously schedul...

JavaScript is required to unlock solutions. Please enable JavaScript and reload the page, or download the source files from GitHub and run the code locally. Goal After this exercise, you should be able to define search spaces for learning algorithms and apply different hyperparameter (HP) optimization (HPO) techniques to search ...