Fits DBN model with fixed sender/receiver effects
Usage
dbn_static(
Y,
family = c("ordinal", "gaussian", "binary"),
nscan = 10000,
burn = 1000,
odens = 1,
seed = 6886,
verbose = TRUE,
previous = NULL,
init = NULL,
symmetric = FALSE
)Arguments
- Y
Data array (nodes x nodes x relations x time)
- family
Character string specifying the data family/distribution:
"ordinal": Ordinal data (ordered categories). Data should be positive integers.
"gaussian": Continuous data with Gaussian errors. Data can be any real numbers.
"binary": Binary (0/1) data. Data should be 0/1 or logical values.
- nscan
Number of iterations of the Markov chain (beyond burn-in)
- burn
Burn-in for the Markov chain
- odens
Output density for the Markov chain
- seed
Random seed for reproducibility
- verbose
Logical or numeric. TRUE prints every 100 iterations, numeric prints every n iterations, FALSE suppresses output.
- previous
Previous dbn_static results to continue from (optional)
- init
List of initial values for parameters: B, s2, t2, g2, M, Z (optional)
- symmetric
Logical. If TRUE, store symmetric flag in output dims. Default: FALSE.
See also
dbn for the main dispatcher, param_summary for posterior summaries
Examples
# \donttest{
sim <- simulate_static_dbn(n = 8, time = 5, seed = 1)
fit <- dbn_static(sim$Y, nscan = 200, burn = 100, verbose = FALSE)
# }