greta: greta: simple and scalable statistical modelling in R

In goldingn/greta: Simple and Scalable Statistical Modelling in R

Description

greta lets you write statistical models interactively in native R code, then sample from them efficiently using Hamiltonian Monte Carlo.

The computational heavy lifting is done by TensorFlow, Google's automatic differentiation library. So greta is particularly fast where the model contains lots of linear algebra, and greta models can be run across CPU clusters or on GPUs.

See the simple example below, and take a look at the greta website for more information including tutorials and examples.

Examples

## Not run: 
# a simple Bayesian regression model for the iris data

# priors
int <- normal(0, 5)
coef <- normal(0, 3)
sd <- lognormal(0, 3)

# likelihood
mean <- int + coef * iris$Petal.Length
distribution(iris$Sepal.Length) <- normal(mean, sd)

# build and sample
m <- model(int, coef, sd)
draws <- mcmc(m, n_samples = 100)

## End(Not run)

goldingn/greta documentation built on May 24, 2021, 11 a.m.