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Numerical optimization of the 2ts model

Source: R/fit2tsmodel_ucminf.R
fit2tsmodel_ucminf.Rd

fit2tsmodel_ucminf() performs a numerical optimization of the AIC or BIC of the two time scales model.

It finds the optimal values of log_10(rho_u) and log_10(rho_s) and returns the estimated optimal model. See also ucminf::ucminf().

Usage

fit2tsmodel_ucminf(
  Y,
  R,
  Z = NULL,
  optim_criterion = c("aic", "bic"),
  lrho = c(0, 0),
  Bu,
  Bs,
  Iu,
  Is,
  Du,
  Ds,
  Wprior = NULL,
  ridge = 0,
  control_algorithm = list()
)

Arguments

Y

A matrix (or 3d-array) of event counts of dimension nu by ns (or nu by ns by n).

R

A matrix (or 3d-array) of exposure times of dimension nu by ns (or nu by ns by n).

Z

(optional) A regression matrix of covariates values of dimensions n by p.

optim_criterion

The criterion to be used for optimization: "aic" (default) or "bic".

lrho

A vector of two elements, the initial values for \(\log_{10}(\varrho_u)\) and \(\log_{10}(\varrho_s)\).

Bu

A matrix of B-splines for the u time scale of dimension nu by cu.

Bs

A matrix of B-splines for the s time scale of dimension ns by cs.

Iu

An identity matrix of dimension nbu by nbu.

Is

An identity matrix of dimension nbs by nbs.

Du

The difference matrix over u.

Ds

The difference matrix over s.

Wprior

An optional matrix of a-priori weights.

ridge

A ridge penalty parameter: default is 0. This is useful when, in some cases the algorithm shows convergence problems. In this case, set to a small number, for example 1e-4.

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 is 1e-5.

  • verbose A Boolean. Default is FALSE. If TRUE monitors the iteration process.

  • monitor_ev A Boolean. Default is FALSE. If TRUE monitors the evaluation of the model over the log_10(rho_s) values.

Value

An object of class haz2ts with the following elements:

  • optimal_model A list containing the results of the optimal model.

  • optimal_logrho A vector with the optimal values of log10(rho_u) and log10(rho_s).

  • P_optimal The optimal penalty matrix P.

References

Nielsen H, Mortensen S (2024). ucminf: General-Purpose Unconstrained Non-Linear Optimization. R package version 1.2.2, https://CRAN.R-project.org/package=ucminf