Description Usage Arguments Value
MCMC algorithm using Gibbs sampling for each variable with structural NA
1 2 3 |
Y |
relational array of relations |
X |
Time x n x n x p covariate array |
RE |
random effect to be included ("additive" and/or "multiplicative") |
R |
dimension of the multiplicative effects |
dist |
standard Exponential or squared Exponential |
gammapriors |
inverse-gamma shape and scale parameters for (s2, beta, theta, d) |
avail |
Time x n matrix reperesenting the availibility of nodes (1 if avail, 0 if structural NA) |
burn |
burn in for the Markov chain |
nscan |
number of iterations of the Markov chain (beyond burn-in) |
odens |
output density for the Markov chain |
kappas |
P+2 length vector of GP length parameters |
Final estimate of the parameters
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