meanStdGMCMC | R Documentation |
meanStdGMCMC
mean standardizes the posterior distribution of a
variance matrix (e.g. a G-matrix)
meanStdGMCMC(G_mcmc, means_mcmc)
G_mcmc |
A posterior distribution of a variance matrix in the form of a
table. Each row in the table must be one iteration of the posterior
distribution (or bootstrap distribution). Each iteration of the matrix must
be on the form as given by |
means_mcmc |
A posterior distribution of a vector of means in the form
of a table. Each row in the table must be one iteration of the posterior
distribution (or bootstrap distribution). A posterior distribution of a
mean vector in the slot |
The posterior distribution of a mean standardized variance matrix.
Geir H. Bolstad
# Simulating a posterior distribution # (or bootstrap distribution) of a G-matrix: G <- matrix(c(1, 1, 0, 1, 4, 1, 0, 1, 2), ncol = 3) G_mcmc <- sapply(c(G), function(x) rnorm(10, x, 0.01)) G_mcmc <- t(apply(G_mcmc, 1, function(x) { G <- matrix(x, ncol = sqrt(length(x))) G[lower.tri(G)] <- t(G)[lower.tri(G)] c(G) })) # Simulating a posterior distribution # (or bootstrap distribution) of trait means: means <- c(1, 1.4, 2.1) means_mcmc <- sapply(means, function(x) rnorm(10, x, 0.01)) # Mean standardizing the G-matrix: meanStdGMCMC(G_mcmc, means_mcmc)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.