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

Description Usage Arguments Value Examples

View source: R/corMat.R

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

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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

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

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