Downloads provided by UsageCounts
This is the first full draft containing brms versions of all of Kruschke's JAGS and Stan models, excluding examples that are not possible with the brms paradigm. Noteworthy changes include: two new solutions for the conditional logistic models of Chapter 22 thanks to the generous efforts by Henrik Singmann and Mattan Ben-Shachar; replacing the depreciated posterior_samples() function with the new posterior::as_draws_df()-based workflow; adding a new solution for the multivariate Bernoulli model with different trial numbers via the resp_subset() function in Section 7.4.4.1; improving the efficiency of the intercept-only Bernoulli models with the new lb and ub arguments for priors of class = Intercept; updating all model fits with brms version 2.17.0; and various minor code, hyperlink, and typo corrections.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 2 | |
| downloads | 1 |

Views provided by UsageCounts
Downloads provided by UsageCounts