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Update ci.yml (#57)
* Update ci.yml * Update README.md * Update Project.toml * Update fit.jl * Update ci.yml * Update Project.toml * Update ci.yml * Update factormodel.jl * Update factormodel.jl * update * Update fit.jl
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‎.github/workflows/ci.yml

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@@ -7,27 +7,30 @@ on:
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branches:
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- master
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tags: '*'
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workflow_dispatch:
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jobs:
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test:
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name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
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runs-on: ${{ matrix.os }}
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continue-on-error: ${{ matrix.version == 'nightly' }}
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strategy:
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fail-fast: false
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matrix:
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version:
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- '1.6' # Replace this with the minimum Julia version that your package supports. E.g. if your package requires Julia 1.5 or higher, change this to '1.5'.
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- '1' # Leave this line unchanged. '1' will automatically expand to the latest stable 1.x release of Julia.
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- '1.9'
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- '1'
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# - 'nightly'
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os:
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- ubuntu-latest
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arch:
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- x64
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steps:
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- uses: actions/checkout@v2
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- uses: julia-actions/setup-julia@v1
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- uses: actions/checkout@v4
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- uses: julia-actions/setup-julia@v2
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: actions/cache@v1
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- uses: actions/cache@v4
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env:
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cache-name: cache-artifacts
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with:
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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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- uses: codecov/codecov-action@v1
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- uses: codecov/codecov-action@v5
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with:
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file: lcov.info
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files: lcov.info
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# docs:
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# name: Documentation
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# runs-on: ubuntu-latest
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# steps:
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# - uses: actions/checkout@v4
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# - uses: julia-actions/setup-julia@v2
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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: |
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# julia --project=docs -e '
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# using Documenter: doctest
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# using ForwardDiff
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# doctest(ForwardDiff)'
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# - run: julia --project=docs docs/make.jl
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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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name = "InteractiveFixedEffectModels"
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uuid = "80307280-efb2-5c5d-af8b-a9c15821677b"
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version = "1.2.2"
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version = "1.3.0"
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[deps]
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DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
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[compat]
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DataFrames = "0.21, 0.22, 1"
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FillArrays = "0.7, 0.8, 0.9, 0.10, 0.11, 0.12, 0.13, 1"
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FixedEffectModels = "1.5"
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FixedEffectModels = "1.11"
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FixedEffects = "2"
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GroupedArrays = "0.3"
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LeastSquaresOptim = "0.7, 0.8"
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StatsFuns = "0.9, 1"
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Tables = "1"
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Vcov = "0.8"
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julia = "1.6"
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julia = "1.9"
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[extras]
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CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"

‎README.md

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[![Build Status](https://travis-ci.com/FixedEffects/InteractiveFixedEffectModels.jl.svg?branch=master)](https://travis-ci.com/FixedEffects/InteractiveFixedEffectModels.jl)
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[![Build status](https://github.com/matthieugomez/InteractiveFixedEffectModels.jl/workflows/CI/badge.svg)](https://github.com/matthieugomez/InteractiveFixedEffectModels.jl/actions)
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[![Coverage Status](https://coveralls.io/repos/matthieugomez/InteractiveFixedEffectModels.jl/badge.svg?branch=master&service=github)](https://coveralls.io/github/matthieugomez/InteractiveFixedEffectModels.jl?branch=master)
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## Installation

‎test/factormodel.jl

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using DataFrames, InteractiveFixedEffectModels,Test, CSV
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df = df = DataFrame(CSV.File(joinpath(dirname(pathof(InteractiveFixedEffectModels)), "../dataset/Cigar.csv")))
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df = DataFrame(CSV.File(joinpath(dirname(pathof(InteractiveFixedEffectModels)), "../dataset/Cigar.csv")))
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for method in [:gauss_seidel, :dogleg, :levenberg_marquardt]
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println(method)
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model = @formula Sales ~ 0 + ife(State, Year, 1)
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result = regife(df, model, method = method, maxiter = 10_000)
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result = regife(df, model, method = method, maxiter = 10_000, save = true)
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@test abs(result.augmentdf[1, :factors1]) ≈ 0.18662770198472406 atol = 1e-1
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@test abs(result.augmentdf[1, :loadings1]) ≈ 587.2272 atol = 1e-1
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@test result.augmentdf[1, :residuals] ≈ - 15.6928 atol = 1e-1
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model = @formula Sales ~ 0 + ife(State, Year, 2)
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result = regife(df, model, method = method, maxiter = 10_000)
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result = regife(df, model, method = method, maxiter = 10_000, save = true)
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@test abs(result.augmentdf[1, :factors1]) ≈ 0.18662770198472406 atol = 1e-1
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@test abs(result.augmentdf[1, :loadings1]) ≈ 587.227 atol = 1e-1
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@test result.augmentdf[1, :residuals] ≈ 2.16611 atol = 1e-1
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model = @formula Sales ~ ife(State, Year, 1) + fe(State)
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result = regife(df, model, method = method, maxiter = 10_000)
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result = regife(df, model, method = method, maxiter = 10_000, save = true)
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@test abs(result.augmentdf[1, :factors1]) ≈ 0.17636 atol = 1e-1
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@test abs(result.augmentdf[1, :loadings1]) ≈ 20.176432452716522 atol = 1e-1
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@test result.augmentdf[1, :residuals] ≈ - 10.0181 atol = 1e-1
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@test result.augmentdf[1, :fe_State] ≈ 107.4766 atol = 1e-1
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model = @formula Sales ~ ife(State, Year, 2) + fe(State)
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result = regife(df, model, method = method, maxiter = 10_000)
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result = regife(df, model, method = method, maxiter = 10_000, save = true)
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@test abs(result.augmentdf[1, :factors2]) ≈ 0.244 atol = 1e-1
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@test abs(result.augmentdf[1, :loadings2]) ≈ 49.7943 atol = 1e-1
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@test result.augmentdf[1, :residuals] ≈ 2.165319 atol = 1e-1
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@test result.augmentdf[1, :fe_State] ≈ 107.47666 atol = 1e-1
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model = @formula Sales ~ ife(State, Year, 2) + fe(State)
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result = regife(df, model, subset = df.State .<= 30, method = method, maxiter = 10_000)
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result = regife(df, model, subset = df.State .<= 30, method = method, maxiter = 10_000, save = true)
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@test size(result.augmentdf, 1) == size(df, 1)
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@test abs(result.augmentdf[1, :factors1]) ≈ 0.20215 atol = 1e-1
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@test abs(result.augmentdf[1, :loadings1]) ≈ 29.546 atol = 1e-1

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