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Fit a Koenker-Mizera (KM) model for a contingency table.

Source: R/pvEBayes_main_function.R
dot-KM_fit.Rd

Fit a Koenker-Mizera (KM) model for a contingency table.

Usage

.KM_fit(
  N,
  E,
  rtol_KM = 1e-04,
  km_optimizer = c("ECOS", "CLARABEL", "SCS"),
  ...
)

Arguments

N

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

E

A matrix of expected counts under the null model for the SRS frequency table.

rtol_KM

The relative tolerance on the duality gap.

km_optimizer

Character vector specifying the optimizer(s) used to fit the KM model. Supported values are "ECOS", "CLARABEL", and "SCS". If multiple optimizers are supplied, they are tried sequentially and the first successfully fitted result is returned. Defaults to c("ECOS", "CLARABEL", "SCS")`.

...

additional parameters to be passed to optimizer for 'KM' model. See 'CVXR::solve' for detail.

Value

a list of CVXR optimizer outputs

Details

Parameter estimation for the "KM" model is formulated as a convex optimization problem. The objective function and constraints used in pvEBayes follow the same construction as in REBayes. Parameter estimation is performed using the open-source convex optimization package CVXR. The grid value generation follows the recommendation of Tan et al. (2025).

References

Koenker R, Gu J. REBayes: an R package for empirical Bayes mixture methods. Journal of Statistical Software. 2017; 4;82:1-26.

Tan Y, Markatou M and Chakraborty S. Flexible Empirical Bayesian Approaches to Pharmacovigilance for Simultaneous Signal Detection and Signal Strength Estimation in Spontaneous Reporting Systems Data. Statistics in Medicine. 2025; 44: 18-19, https://doi.org/10.1002/sim.70195.

Fu, A, Narasimhan, B, Boyd, S. CVXR: An R Package for Disciplined Convex Optimization. Journal of Statistical Software. 2020; 94;14:1-34.