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Merge StatsBase into Statistics
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.github/workflows/ci.yml

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${{ runner.os }}-test-${{ env.cache-name }}-
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${{ runner.os }}-test-
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${{ runner.os }}-
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<<<<<<< HEAD
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=======
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- run: julia --color=yes .ci/test_and_change_uuid.jl
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>>>>>>> master
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- uses: julia-actions/julia-buildpkg@v1
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- uses: julia-actions/julia-runtest@v1
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- uses: julia-actions/julia-processcoverage@v1
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- uses: julia-actions/julia-buildpkg@latest
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- uses: julia-actions/julia-docdeploy@latest
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=======
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- uses: julia-actions/setup-julia@v1
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with:
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version: '1'
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- run: |
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julia --project=docs -e '
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using Pkg
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Pkg.develop(PackageSpec(path=pwd()))
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Pkg.instantiate()'
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- run: julia --project=docs docs/make.jl
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>>>>>>> master
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }}

Project.toml

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[deps]
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LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
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Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
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SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
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[extras]
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Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
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Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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[targets]
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test = ["Random", "Test"]
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test = ["Dates", "Random", "Test"]

docs/Project.toml

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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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[compat]
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Documenter = "0.24"
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Documenter = "0.27"

docs/make.jl

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using Documenter, Statistics
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using Documenter, Statistics, Random
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# Workaround for JuliaLang/julia/pull/28625
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if Base.HOME_PROJECT[] !== nothing
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Base.HOME_PROJECT[] = abspath(Base.HOME_PROJECT[])
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end
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makedocs(
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sitename = "Statistics.jl",
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modules = [Statistics],
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sitename = "Statistics",
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pages = Any[
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"Statistics" => "index.md"
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]
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)
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pages = ["index.md",
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"weights.md",
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"scalarstats.md",
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"cov.md",
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"robust.md",
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"ranking.md",
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"empirical.md"]
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)
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deploydocs(repo = "github.com/JuliaLang/Statistics.jl.git")
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deploydocs(
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repo = "github.com/JuliaLang/Statistics.jl.git"
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)

docs/src/counts.md

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docs/src/cov.md

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# Scatter Matrix and Covariance
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# Covariances and Correlations
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This package implements functions for computing scatter matrix, as well as weighted covariance matrix.
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Functions to computing various types of covariances and correlations are provided.
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## Covariance, Correlation and Scatter Matrix
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```@docs
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scattermat
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cov
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cov(::CovarianceEstimator, ::AbstractVector)
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cov(::CovarianceEstimator, ::AbstractVector, ::AbstractVector)
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cov(::CovarianceEstimator, ::AbstractMatrix)
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cor
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mean_and_cov
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scattermat
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cov2cor
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cor2cov
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CovarianceEstimator
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SimpleCovariance
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```
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## Partial Correlation
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```@docs
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partialcor
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```
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## Autocovariance and Autocorrelation
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```@docs
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autocov
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autocov!
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autocor
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autocor!
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```
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## Cross-covariance and Cross-correlation
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```@docs
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crosscov
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crosscov!
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crosscor
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crosscor!
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```
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## Partial Autocorrelation Function
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```@docs
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pacf
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pacf!
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```

docs/src/deviation.md

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docs/src/empirical.md

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# Empirical Estimation
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# Empirical Estimation of Distributions
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## Histograms
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```@docs
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merge!
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merge
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midpoints
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norm
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normalize
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normalize!

docs/src/index.md

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# Statistics
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The Statistics standard library module contains basic statistics functionality.
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```@meta
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DocTestSetup = :(using Statistics)
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```
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The Statistics module contains basic statistics functionality: mean, median, quantiles,
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standard deviation, variance, skewness, kurtosis, correlation and covariance.
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Statistics can be weighted, and several weights types are distinguished to apply appropriate
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corrections where necessary.
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```@docs
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std
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stdm
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var
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varm
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cor
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cov
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mean!
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mean
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median!
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median
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middle
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quantile!
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quantile
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```@contents
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Pages = ["weights.md", "scalarstats.md", "cov.md", "robust.md", "ranking.jl",
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"empirical.md"]
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Depth = 2
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```

docs/src/misc.md

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