Skip to main content

StanCon 2020 program is now online!

This year’s Stan Conference is on August 13, 2020 (next Thursday)! The program has been finalized and is online. So far, we’re at 89 registrants spanning across 17 countries!

Registration is $50, which includes swag. There are scholarships available for those that need financial support. If you’re a Stan developer, there’s a discount (see the forums).

Our vision for this year’s conference:

  • All virtual.
    We’re trying our best to enable the interactions at StanCon that make the event special. We’re using a service, Remo, that has tables where people can gather around and chat.
  • Global and inclusive.
    There are 3 sessions that last 2-3 hours that are spaced 8 hours apart. Each session has its own plenary speaker and six discussions (total: 3 plenaries, 18 contributed talks, and 4 developer talks). One of the contributed talks will be recorded in 6 languages (English, Catalan, Spanish, Hindi, French, Finnish)!
  • The format.
    All contributed talks will be distributed and available prior to the conference. For each contributed talk, there will be a 10 minute live Q&A with the presenter and a discussant. During the conference, we’re debuting the plenary talks and developer talks.

Thank you to Metrum Research Group for being our first sponsor!
If you’d like to sponsor StanCon, please email stancon@mc-stan.org. Sponsorship goes towards scholarships and the cost of running the conference.



from Statistical Modeling, Causal Inference, and Social Science https://ift.tt/2BUuCjq
via IFTTT

Comments

Popular posts from this blog

Controlling legend appearance in ggplot2 with override.aes

[This article was first published on Very statisticious on Very statisticious , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. In ggplot2 , aesthetics and their scale_*() functions change both the plot appearance and the plot legend appearance simultaneously. The override.aes argument in guide_legend() allows the user to change only the legend appearance without affecting the rest of the plot. This is useful for making the legend more readable or for creating certain types of combined legends. In this post I’ll first introduce override.aes with a basic example and then go through three additional plotting scenarios to how other instances where override.aes comes in handy. Table of Contents R packages Introducing override.aes Adding a guides() layer Using the guide argument in scale_*() Changing multiple aesthetic par...

Using RStudio and LaTeX

(This article was first published on r – Experimental Behaviour , and kindly contributed to R-bloggers) This post will explain how to integrate RStudio and LaTeX, especially the inclusion of well-formatted tables and nice-looking graphs and figures produced in RStudio and imported to LaTeX. To follow along you will need RStudio, MS Excel and LaTeX. Using tikzdevice to insert R Graphs into LaTeX I am a very visual thinker. If I want to understand a concept I usually and subconsciously try to visualise it. Therefore, more my PhD I tried to transport a lot of empirical insights by means of  visualization . These range from histograms, or violin plots to show distributions, over bargraphs including error bars to compare means, to interaction- or conditional effects of regression models. For quite a while it was very tedious to include such graphs in LaTeX documents. I tried several ways, like saving them as pdf and then including them in LaTeX as pdf, or any other file ...