Description Usage Arguments Details Value Examples
View source: R/centered_precgen2.R
This function generates a precision matrix for a centered (every node in level 1 has the same number of children nodes) 2-level Gaussian hierarchical model (level 0 being the root, and level 3 being the observations) given the variances for each level tau, tau_a, tau_b and sigma_2. It takes advantage of the sparse structure of the precision matrix for centered 2-level gaussian hierarchical models and returns only the non-zero entries of the precision matrix together with its corresponding indices.
1 2 | centered_precgen2(i, j, flat_prior = TRUE, tau = 1, tau_a = 1,
tau_b = 1, sigma_2 = 1)
|
i |
number of nodes at level 1 |
j |
number of children nodes in level 2 per node at level 1 |
flat_prior |
determines whether to use the density with flat prior |
tau |
variance of the root (level 0) |
tau_a |
variance for parameters in level 1 |
tau_b |
variance for parameters in level 2 |
sigma_2 |
variance of the observations |
Assumptions: - variances are constant for parameters within the same level - all observations y_ij are equal to 0 - the mean of the root parameter B is mu = 0
list of non-zero entries of the precision matrix together with its corresponding indices
1 2 3 | i <- 2
j <- 3
centered_precgen2(i = i, j = j)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.