Description Usage Arguments Value Author(s) Examples
The sample.beta
function generates the effect
size estimates of a chosen model within the best models.
1 | sample.beta(x, res.g, Nmonte.sigma = 1, Nmonte = 1)
|
x |
an object of class |
res.g |
an object of class |
Nmonte.sigma |
number of re-samples of the posterior variance
covariance matrix of the outcomes (Sigma), for a given value of
|
Nmonte |
number of re-samples of the regression coefficient
vector, for a given value of |
A list containing the sampled values of the regression
coefficients. Re-samples for a given value of g
among those
observed for the model under investigation are presented in rows
(Nmonte x Nmonte.sigma
rows) and columns are arranged such
that the k-th block of q
values represents the regression
coefficients of predictor k
for all q
outcomes.
Benoit Liquet, b.liquet@uq.edu.au,
Marc Chadeau-Hyam m.chadeau@imperial.ac.uk,
Leonardo
Bottolo l.bottolo@imperial.ac.uk,
Gianluca Campanella
g.campanella11@imperial.ac.uk
1 2 3 4 5 | modelY_Hopx <- example.as.ESS.object()
n.sweep <- get.sweep.best.model(modelY_Hopx,models=1:2)
res.g <- get.g.sweep(modelY_Hopx,n.sweep$result,model=1)
beta <- sample.beta(modelY_Hopx,res.g,Nmonte=5,Nmonte.sigma=5)
res.D14Mit3 <- boxplotbeta(modelY_Hopx,beta,variable="D14Mit3")
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.