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Select hyperparameter (p, c0) and obtain the optimal efron model based on AIC and BIC

Source: R/pvEBayes_main_function.R
tuning_efron.Rd

Select hyperparameter (p, c0) and obtain the optimal efron model based on AIC and BIC

Usage

tuning_efron(
  contin_table,
  p_vec = NULL,
  c0_vec = NULL,
  return_all_fit = FALSE,
  return_all_AIC = TRUE,
  return_all_BIC = TRUE,
  rtol_efron = 1e-10
)

Arguments

contin_table

an IxJ contingency table showing pairwise counts of adverse events for I AEs (along the rows) and J drugs (along the columns).

p_vec

vector of hyperparameter p values to be selected. p is a hyperparameter in "efron" model which should be a positive integer. If is NULL, a default set of p values (40, 60, 80, 100, 120) will be used.

c0_vec

vector of hyperparameter c0 values to be selected. c0 is a hyperparameter in "efron" model which should be a positive number. If is NULL, a default set of c0 values (0.001, 0.01, 0.1, 0.2, 0.5) will be used.

rtol_efron

a tolerance parameter used when 'efron' model is fitted. Default to 1e-10. See 'stats::nlminb' for detail.

Value

a list of fitted models with hyperparameter alpha selected by AIC or BIC.

References

Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control. 2003; 19(6):716-23.

Schwarz G. Estimating the dimension of a model. The Annals of Statistics. 1978; 1:461-4.