ihw_naive: IHW wrappers

Description Usage Arguments Details Value Functions Examples

View source: R/ddhw_wrappers.R

Description

IHW wrappers

Usage

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ihw_naive(unadj_p, filterstat, alpha)

ihw_ecdf_5fold(unadj_p, filterstat, alpha)

ihw_5fold(unadj_p, filterstat, alpha)

ihw_5fold_reg(unadj_p, filterstat, alpha)

ihw_bonf_5fold_reg(unadj_p, filterstat, alpha)

ihw_storey_5fold(unadj_p, filterstat, alpha)

Arguments

unadj_p

Numeric vector of unadjusted p-values.

filterstat

Factor to which different hypotheses belong

alpha

Significance level at which to apply method

Details

These are closures, which apply IHW with custom prespecified parameters. These correspond to interesting settings, for which it is convenient to be able to immediately call the corresponding functions, rather than having to specify parameters each time. Thus they make it easier to benchmark. All of these wrappers are defined in 2 lines of code, so the settings pertaining to each one can be inspected by typing the functions name into the console.

Value

ihwResult multiple testing object

Functions

Examples

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     sim_df <- du_ttest_sim(20000,0.95, 1.5)
     obj <- ihw_5fold(sim_df$pvalue, sim_df$filterstat, .1)
     sum(rejected_hypotheses(obj))

nignatiadis/ihwPaper documentation built on Jan. 18, 2021, 3:13 p.m.