get_normal: Normal model

In pierrejacob/winference: Approximate Bayesian Computation with the Wasserstein distance

Description

This function returns a list representing a Normal location model. The prior is mu ~ Normal(mu_0, nu^-1), where nu is precision and tau ~ Gamma(alpha, beta), where beta is rate (1/scale). The likelihood is Y ~ Normal(mu, tau^2) where tau^2 is the variance.

Usage

get_normal()

Value

The list contains rprior, dprior (generate and evaluate the density of prior distribution), generate_randomness (generate data-generating variables), robservation (create synthetic data sets), parameter_names (useful for plotting), thetadim (dimension of parameter), ydim (dimension of observations), parameters (list of hyperparameters, to be passed to rprior,dprior,robservation)

pierrejacob/winference documentation built on Feb. 17, 2020, 10:28 p.m.