cause_grid_approx: CAUSE with grid approximation and fixed rho

In jean997/sherlockAsh: CAUSE: Causal Analysis Using Summary Effect Estimates

Description

CAUSE with grid approximation and fixed rho

Usage

cause_grid_approx(dat, seed, mix_grid, rho, brange = c(-1, 1),
  nb = 100, nq = 100, z_prior_func = function(z) {     dnorm(z, 0,
  0.5, log = TRUE) }, b_prior_func = function(b) {     dnorm(b, 0, 0.6,
  log = TRUE) }, q_prior_func = function(q) {     dbeta(q, 0.1, 1, log =
  TRUE) }, waic_samps = 1000, models = 2:3)

Arguments

dat	Data (data.frame)
seed	Seed. Optional.
mix_grid	Grid of mixture parameters. Will be estimated if not provided.
rho	rho
z_prior_func	optional. Unneccessary if you provide rho. Defaults to N(0, 0.5).
b_prior_func	prior function for b. Defaults to N(0, 0.6)
q_prior_func	prior function for q. Defaults to Beta(0.1, 1)
waic_samps	Number of samples for calculating waic
models	Which models to run. 2=causal, 3=shared. Some subset of c(2,3).
bvals	Grid of values for b
qvals	Grid of values for q

jean997/sherlockAsh documentation built on May 18, 2019, 11:45 p.m.