Get fitted object from MCMC results
Usage
get_fit_object(
APS,
BPS,
UVPS,
YPS,
BETA,
VC,
GOF,
Xlist,
actorByYr,
colActorByYr = NULL,
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,
Y_obs = NULL,
G = NULL,
dynamic_beta = FALSE,
beta_dynamic_mask = NULL,
beta_dynamic_groups = NULL,
rho_beta = NULL,
sigma_beta = NULL,
RHO_BETA = NULL,
SIGMA_BETA = NULL,
dynamic_rho = FALSE,
RHO = NULL,
rho_path = 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. In bipartite mode this is the per-year list of row actors.
- colActorByYr
Bipartite only. List of column actors by time point; defaults to
NULL(unipartite).- 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)
- Y_obs
original observed network (stored for residuals computation)
- G
bipartite interaction matrix mapping row to column latent spaces
- dynamic_beta
logical or scalar; whether the BETA storage is 3-D (dynamic_beta path). Default
FALSE.- beta_dynamic_mask
logical vector marking which coefficients are dynamic.
- beta_dynamic_groups
character vector of per-coefficient block labels ("intercept", "dyad", "row", "col");
""for static coefficients.- rho_beta
named numeric vector of per-block AR(1) rho values (one per dynamic block).
- sigma_beta
named numeric vector of per-block AR(1) innovation standard deviations.
- RHO_BETA
matrix of per-iteration rho_beta draws (rows = MCMC draw, cols = dynamic block).
- SIGMA_BETA
matrix of per-iteration sigma_beta draws.
- dynamic_rho
logical indicating whether residual dyadic reciprocity varies by period.
- RHO
matrix of per-iteration, per-period dyadic reciprocity draws.
- rho_path
numeric vector of period-specific dyadic reciprocity values.