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Add package features to documentation
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docs/src/index.md

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## Package Features
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The `MultipleTesting` package offers common algorithms for p-value adjustment
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and combination as well as the estimation of the proportion π₀ of true null
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hypotheses.
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![xkcd p-value guide](https://imgs.xkcd.com/comics/p_values.png)
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## Features
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### Adjustment of p-values
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* Bonferroni
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* Benjamini-Hochberg
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* Adaptive Benjamini-Hochberg with known π₀ or π₀ estimation method (see section below)
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* Benjamini-Yekutieli
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* Benjamini-Liu
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* Hochberg
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* Holm
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* Hommel
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* Sidak
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* Forward Stop
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* Barber-Candès
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```julia
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adjust(pvals, Bonferroni())
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adjust(pvals, BenjaminiHochberg())
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adjust(pvals, BenjaminiHochbergAdaptive(0.9))
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adjust(pvals, BenjaminiHochbergAdaptive(Storey()))
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adjust(pvals, BenjaminiYekutieli())
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adjust(pvals, BenjaminiLiu())
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adjust(pvals, Hochberg())
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adjust(pvals, Holm())
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adjust(pvals, Hommel())
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adjust(pvals, Sidak())
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adjust(pvals, ForwardStop())
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adjust(pvals, BarberCandes())
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```
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The adjustment can also be performed on the `k` smallest out of `n` p-values:
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```julia
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adjust(pvals, n, PValueAdjustmentMethod)
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```
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### Estimation of π₀
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* Storey
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* Storey's closed-form bootstrap
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* Least Slope
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* Two Step
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* RightBoundary (Storey's estimate with dynamically chosen λ)
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* Beta-Uniform Mixture (BUM)
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* Censored BUM
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* Flat Grenander
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* Oracle for known π₀
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```julia
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estimate_pi0(pvals, Storey())
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estimate_pi0(pvals, StoreyBootstrap())
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estimate_pi0(pvals, LeastSlope())
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estimate_pi0(pvals, TwoStep())
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estimate_pi0(pvals, TwoStep(0.05))
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estimate_pi0(pvals, TwoStep(0.05, BenjaminiHochbergAdaptive(0.9))
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estimate_pi0(pvals, RightBoundary())
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estimate_pi0(pvals, CensoredBUM())
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estimate_pi0(pvals, BUM())
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estimate_pi0(pvals, FlatGrenander())
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estimate_pi0(pvals, Oracle(0.9))
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```
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### Combination of p-values
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* Fisher
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* Stouffer, optionally with weights
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* Logit
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* Tippett
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* Simes
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* Wilkinson
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* Minimum of adjusted p-values
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```julia
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combine(pvals, FisherCombination())
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combine(pvals, StoufferCombination())
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combine(pvals, weights, StoufferCombination())
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combine(pvals, LogitCombination())
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combine(pvals, TippettCombination())
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combine(pvals, SimesCombination())
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combine(pvals, WilkinsonCombination(rank))
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combine(pvals, MinimumCombination(PValueAdjustment()))
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```
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### Higher criticism
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* Higher criticism scores
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* Higher criticism threshold
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```julia
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estimate(pvals, HigherCriticismScores())
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estimate(pvals, HigherCriticismThreshold())
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```
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## Manual
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