get_bic_fit_1d()
fits the 1ts model with or without individual
level covariates and it returns the BIC of the model.
See also fit1tsmodel_ucminf()
and fit1ts()
.
Usage
get_bic_fit_1d(
lrho,
r,
y,
Z = NULL,
Bs,
Ds,
Wprior = NULL,
control_algorithm = list(maxiter = 20, conv_crit = 1e-05, verbose = FALSE, monitor_ev =
FALSE)
)
Arguments
- lrho
A starting value for \(\log_{10}(\varrho_s)\). Default is 0.
- r
A vector of exposure times of length ns, or an array of dimension ns by n.
- y
A vector of event counts of length ns, or an array of dimension ns by n.
- Z
(optional) A regression matrix of covariates of dimension n by p.
- Bs
A matrix of B-splines for the time scale
s
.- Ds
The difference matrix of the penalty.
- Wprior
An optional vector of a-priori weights.
- control_algorithm
A list with optional values for the parameters of the iterative processes:
maxiter
The maximum number of iteration for the IWSL algorithm. Default is 20.conv_crit
The convergence criteria, expressed as difference between estimates at iteration i and i+1. Default is1e-5
.verbose
A Boolean. Default isFALSE
. IfTRUE
monitors the iteration process.monitor_ev
A Boolean. Default isFALSE
. IfTRUE
monitors the evaluation of the model over thelog_10(rho_s)
values.