tuning_efron: Select hyperparameter (p, c0) and obtain the optimal efron...

In pvEBayes: Empirical Bayes Methods for Pharmacovigilance

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

Description

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
)

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 (80, 100, 120, 150, 200) 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.

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.

pvEBayes documentation built on Aug. 8, 2025, 6:13 p.m.