parameter_selection: Select Optimal Tuning Parameters
In bravo: Bayesian Screening and Variable Selection

parameter_selection

R Documentation

Select Optimal Tuning Parameters

Description

Full training step: cleans SNP matrix and tunes SVEN hyperparameters.

Usage

parameter_selection(
  X,
  R2 = 0.5,
  betamax = 1,
  n.cores = max(1, parallel::detectCores() - 1),
  hitsize = "all",
  MAF_threshold = 0.05
)

Arguments

`X`	Raw SNP matrix (dgCMatrix).
`R2`	Heritability (default 0.5).
`betamax`	Maximum effect size magnitude (default 1).
`n.cores`	Number of cores (default: detectCores() - 1).
`hitsize`	One of "all", "small", "medium", "large" (default "all").
`MAF_threshold`	MAF cutoff (default 0.05).

Value

A list containing the original SNP matrix, cleaned SNP matrix, optimal parameters, MAF threshold, expected hit size, and number of cores used. The list is assigned class "svenetics_trained" for use in downstream functions.

bravo documentation built on May 27, 2026, 5:08 p.m.