06
Sep

2018

2018

2 Comments

This is the third part of my blog series on fitting the 4-parameter Wiener model with brms. The first part discussed how to set up the data and model. The second part was concerned with (mostly graphical) model diagnostics and the assessment of the adequacy (i.e., the fit) of the model. This third part will […]

07
Jan

2018

2018

6 Comments

This is the considerably belated second part of my blog series on fitting diffusion models (or better, the 4-parameter Wiener model) with brms. The first part discusses how to set up the data and model. This second part is concerned with perhaps the most important steps in each model based data analysis, model diagnostics and […]

26
Nov

2017

2017

3 Comments

Stan is probably the most interesting development in computational statistics in the last few years, at least for me. The version of Hamiltonian Monte-Carlo (HMC) implemented in Stan (NUTS, ) is extremely efficient and the range of probability distributions implemented in the Stan language allows to fit an extremely wide range of models. Stan has […]

26
May

2017

2017

2 Comments

It took us quite a while but we have finally released a new version of rtdists to CRAN which provides a few significant improvements. As a reminder, rtdists [p]rovides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation): (a) Ratcliff diffusion model based on C code by Andreas and Jochen Voss and (b) […]

03
Apr

2016

2016

1 Comments

I have just submitted a new version of rtdists to CRAN (v. 0.4-9). As I haven’t mentioned rtdists on here yet, let me simply copy it’s description as a short introduction, a longer introduction follows below: Provides response time distributions (density/PDF, distribution function/CDF, quantile function, and random generation): (a) Ratcliff diffusion model based on C […]