corMat: Correlation Matrix Estimation (also returns partial...

In abnormally-distributed/Bayezilla: Bayesian Models With JAGS and Several Utilities for Data Exploration and Model Evaluation.

Description

Just a simple multivariate norma-wishart conjugate model that returns the standardized inverse precision matrix (correlation matrix) and standardized precision matrix (partial correlations).

Usage

corMat(x, df = "default", iter = 4000, warmup = 2500, adapt = 2500,
  chains = 4, thin = 1, method = "parallel", cl = makeCluster(2),
  ...)

Arguments

x	a data frame or matrix
df	degrees of freedom for wishart prior. Defaults to ncol(X) + 1
iter	the number of iterations. defaults to 4000.
warmup	number of burnin samples. defaults to 2500.
adapt	number of adaptation steps. defaults to 2500.
chains	number of chains. defaults to 4.
thin	the thinning interval. defaults to 3.
method	Defaults to "parallel". For an alternative parallel option, choose "rjparallel" or. Otherwise, "rjags" (single core run).
cl	Use parallel::makeCluster(# clusters) to specify clusters for the parallel methods. Defaults to two cores.
...	other arguments to run.jags

Value

a runjags object

Examples

corMat(iris$Sepal.Width, iris$Petal.Length)

abnormally-distributed/Bayezilla documentation built on Oct. 31, 2019, 1:57 a.m.