Explore >> Select a destination
|
You are here 
|
gregorygundersen.com | ||
| | | | |
www.raynergobran.com
|
|
| | | | | In Monte Carlo integration, it is best to fill as much of the search space as possible with area under the curve to be integrated. | |
| | | | |
poissonisfish.com
|
|
| | | | | Someof the most fundamental functions in R, in my opinion, are those that deal with probability distributions. Whenever you compute a P-value you relyon a probability distribution, and there are many types out there. In this exercise I will cover four: Bernoulli, Binomial, Poisson, and Normal distributions. Let me begin with some theory first: Bernoulli... | |
| | | | |
sriku.org
|
|
| | | | | [AI summary] The article explains how to generate random numbers that follow a specific probability distribution using a uniform random number generator, focusing on methods involving inverse transform sampling and handling both continuous and discrete cases. | |
| | | | |
austinrochford.com
|
|
| | | I recently read the interesting paper The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions on the arXiv and followed its references to the also fascinating Bayesian Regre | ||
