creating greta arrays

Create greta arrays representing observed data or fixed values

create data greta arrays

zeros() ones() greta_array()

convert other objects to greta arrays

as_data()

variables & distributions

Create variables and assign probability distributions over greta arrays

create greta variables

variable() cholesky_variable() simplex_variable() ordered_variable()

probability distributions

uniform() normal() lognormal() bernoulli() binomial() beta_binomial() negative_binomial() hypergeometric() poisson() gamma() inverse_gamma() weibull() exponential() pareto() student() laplace() beta() cauchy() chi_squared() logistic() f() multivariate_normal() wishart() lkj_correlation() multinomial() categorical() dirichlet() dirichlet_multinomial()

define a distribution over data

`distribution<-`() distribution()

mixtures of probability distributions

mixture()

define joint distributions

joint()

manipulating greta arrays

Functions and operations for modifying greta arrays

arithmetic, logical and relational operators for greta arrays

operators

functions for greta arrays

functions

extract, replace and combine greta arrays

extract-replace-combine

transformation functions for greta arrays

iprobit() ilogit() icloglog() icauchit() log1pe() imultilogit()

modelling

Define and visualise models and fit them to data

greta model objects

model() print(<greta_model>) plot(<greta_model>)

statistical inference on greta models

mcmc() stashed_samples() extra_samples() initials() opt()

calculate greta arrays given fixed values

calculate()

MCMC samplers

hmc() rwmh() slice()

optimisation methods

nelder_mead() powell() cg() bfgs() newton_cg() l_bfgs_b() tnc() cobyla() slsqp() gradient_descent() adadelta() adagrad() adagrad_da() momentum() adam() ftrl() proximal_gradient_descent() proximal_adagrad() rms_prop()

extending greta

Write R packages that extend or use greta

internal greta methods

internals