Like rUV_dynamic_fc but the AR(1) innovations are Student-t via a
scale-mixture of normals, a continuous heavy-tailed alternative to snap-shift.
rUV_dynamic_t_fc(
U,
V,
ET,
rho_uv,
sigma_uv,
s2,
nu,
lambda_u = NULL,
lambda_v = NULL,
shrink = TRUE,
symmetric = FALSE
)list with updated U, V arrays and lambda_u, lambda_v local scales
3D array of current U positions (n x R x T)
3D array of current V positions (n x R x T)
3D array of residuals (n x n x T)
AR(1) autoregressive parameter
Innovation scale
dyadic variance
Student-t degrees of freedom
current local scales for U (n x T)
current local scales for V (n x T)
whether to apply shrinkage (default TRUE)
whether the network is symmetric (default FALSE)
Cassy Dorff, Shahryar Minhas, Tosin Salau