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Select hyperparameter alpha and obtain the optimal general-gamma model based on AIC and BIC

Source: R/pvEBayes_main_function.R
tuning_general_gamma.Rd

Select hyperparameter alpha and obtain the optimal general-gamma model based on AIC and BIC

Usage

tuning_general_gamma(
  contin_table,
  alpha_vec = NULL,
  return_all_fit = FALSE,
  return_all_AIC = TRUE,
  return_all_BIC = TRUE,
  tol_ecm = 1e-04
)

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).

alpha_vec

vector of hyperparameter alpha values to be selected. Alpha is hyperparameter in general-gamma model which is numeric and between 0 and 1. If is NULL, a default set of alpha values (0, 0.1, 0.3, 0.5, 0.7, 0.9) will be used.

tol_ecm

a tolerance parameter used for the ECM stopping rule, defined as the absolute change in the joint marginal likelihood between two consecutive iterations. It is used when 'GPS', 'K-gamma' or 'general-gamma' model is fitted. Default to be 1e-4.

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.