Explore >> Select a destination
|
You are here 
|
mc-stan.org | ||
| | | | |
www.civilytics.com
|
|
| | | | | Update: Since this post was released I have co-authored an R package to make some of the items in this post easier to do. This package is called merTools and is available on CRAN and on GitHub. To read more about it, read my new post hereand check out the packageon GitHub. Introduction First of [...] | |
| | | | |
blog.stata.com
|
|
| | | | | You have a model that is nonlinear in the parameters. Perhaps it is a model of tree growth and therefore asymptotes to a maximum value. Perhaps it is a model of serum concentrations of a drug that rise rapidly to a peak concentration and then decay exponentially. Easy enough, use nonlinear regression ([R] nl) to [...] | |
| | | | |
rdrr.io
|
|
| | | | | ||
| | | | |
austinrochford.com
|
|
| | | For some time I have been interested in better understanding the horseshoe prior1 by implementing it in PyMC3. The horsehoe prior is a continuous alternative to the spike-and-slab prior for sparse Bay | ||
