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Numerical optimization of the 1ts model

Source: R/fit1tsmodel_ucminf.R
fit1tsmodel_ucminf.Rd

fit1tsmodel_ucminf() performs a numerical optimization of the AIC or BIC of the one time scale model.

It finds the optimal values of \(\log_{10}(\varrho_s)\) and returns the estimated optimal model. See also ucminf::ucminf().

Usage

fit1tsmodel_ucminf(
  r,
  y,
  Z = NULL,
  lrho = 0,
  Bs,
  Ds,
  Wprior = NULL,
  optim_criterion = c("aic", "bic"),
  control_algorithm = list()
)

Arguments

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.

lrho

A starting value for \(\log_{10}(\varrho_s)\). Default is 0.

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.

optim_criterion

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

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 haz1ts with the following elements:

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

  • optimal_logrho The optimal value of 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