Get fitted object from MCMC results
Usage
get_fit_object(
APS,
BPS,
UVPS,
YPS,
BETA,
VC,
GOF,
Xlist,
actorByYr,
start_vals,
symmetric,
tryErrorChecks,
model.name = NULL,
U = NULL,
V = NULL,
dynamic_uv = FALSE,
dynamic_ab = FALSE,
bip = FALSE,
rho_ab = NULL,
rho_uv = NULL,
family = NULL,
odmax = NULL,
nA = NULL,
nB = NULL,
n_time = NULL
)Arguments
- APS
summed additive sender random effects (or matrix for dynamic)
- BPS
summed additive receiver random effects (or matrix for dynamic)
- UVPS
summed multiplicative random effects
- YPS
summed Y posterior predictive values
- BETA
Matrix of draws for regression coefficient estimates
- VC
Matrix of draws for variance estimates
- GOF
Matrix of draws for goodness of fit calculations
- Xlist
List based version of design array
- actorByYr
List of actors by time point
- start_vals
start_vals for future model run
- symmetric
logical indicating whether model is symmetric
- tryErrorChecks
list with counts of MCMC errors
- model.name
Name of the model (optional)
- U
Latent sender positions (optional, for dynamic UV)
- V
Latent receiver positions (optional, for dynamic UV)
- dynamic_uv
logical indicating whether UV effects are dynamic
- dynamic_ab
logical indicating whether additive effects are dynamic
- bip
logical indicating whether the network is bipartite
- rho_ab
temporal correlation parameter for additive effects (optional)
- rho_uv
temporal correlation parameter for multiplicative effects (optional)
- family
character string specifying the model family (e.g., "binary", "normal", "poisson")
- odmax
vector of maximum ranks for ordinal or fixed rank nomination families
- nA
number of actors in first mode (for bipartite networks)
- nB
number of actors in second mode (for bipartite networks)
- n_time
number of time periods (for longitudinal models)