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Merge branch 'master' of github.com:DoubleML/doubleml-for-r into 0.0.X
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‎.github/workflows/deploy_docu.yml‎

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# Workflow based on https://github.com/r-lib/actions/blob/master/examples/pkgdown.yaml
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name: CI deploy documentation
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on:
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push:
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branches:
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- master
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workflow_dispatch:
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release:
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types:
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- published
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jobs:
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build:
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runs-on: ubuntu-20.04
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steps:
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- uses: actions/checkout@v2
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with:
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persist-credentials: false
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- name: Install SSH Client
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uses: webfactory/ssh-agent@v0.4.1
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with:
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ssh-private-key: ${{ secrets.DEPLOY_KEY }}
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- name: Install R
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uses: r-lib/actions/setup-r@v1
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with:
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r-version: 'release'
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- uses: r-lib/actions/setup-pandoc@v1
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- name: Query dependencies
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run: |
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install.packages('remotes')
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saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2)
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writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), ".github/R-version")
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shell: Rscript {0}
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- name: Cache R packages
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uses: actions/cache@v2
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with:
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path: ${{ env.R_LIBS_USER }}
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key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }}
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restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-
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- name: Install system dependencies package
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run: |
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while read -r cmd
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do
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eval sudo $cmd
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done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "20.04"))')
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- name: Install system dependencies pkgdown
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run: |
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while read -r cmd
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do
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eval sudo $cmd
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done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "20.04", package="pkgdown"))')
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- name: Install additional system dependencies for pkgdown
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run: sudo apt-get install libharfbuzz-dev libfribidi-dev
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- name: Install dependencies
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run: |
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remotes::install_deps(dependencies = TRUE)
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remotes::install_cran("pkgdown")
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shell: Rscript {0}
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- name: Install package
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run: R CMD INSTALL .
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- name: Build docu with pkgdown
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run: Rscript -e 'pkgdown::build_site(new_process = FALSE)'
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- name: Deploy to dev
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if: ${{ github.event_name == 'pull_request' || github.event_name == 'push' }}
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uses: JamesIves/github-pages-deploy-action@3.7.1
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with:
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REPOSITORY_NAME: DoubleML/doubleml.github.io
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BRANCH: master
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FOLDER: docs/dev
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TARGET_FOLDER: r/dev
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GIT_CONFIG_NAME: DoubleML Deploy Bot
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GIT_CONFIG_EMAIL: DoubleML@users.noreply.github.com
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CLEAN: true
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SSH: true
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- name: Deploy to version
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if: ${{ github.event_name == 'release' }}
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uses: JamesIves/github-pages-deploy-action@3.7.1
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with:
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REPOSITORY_NAME: DoubleML/doubleml.github.io
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BRANCH: master
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FOLDER: docs/dev
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TARGET_FOLDER: r/ ${{ github.ref }}
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GIT_CONFIG_NAME: DoubleML Deploy Bot
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GIT_CONFIG_EMAIL: DoubleML@users.noreply.github.com
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CLEAN: true
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SSH: true
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- name: Deploy to stable
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if: ${{ github.event_name == 'release' }}
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uses: JamesIves/github-pages-deploy-action@3.7.1
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with:
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REPOSITORY_NAME: DoubleML/doubleml.github.io
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BRANCH: master
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FOLDER: docs/dev
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TARGET_FOLDER: r/stable
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GIT_CONFIG_NAME: DoubleML Deploy Bot
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GIT_CONFIG_EMAIL: DoubleML@users.noreply.github.com
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CLEAN: true
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SSH: true

‎.github/workflows/deploy_pkg.yml‎

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# Workflow based on https://github.com/r-lib/actions/tree/master/examples#standard-ci-workflow
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name: CI deploy package
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on:
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release:
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types:
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- published
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jobs:
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build:
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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: r-lib/actions/setup-r@v1
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with:
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r-version: 'release'
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- uses: r-lib/actions/setup-pandoc@v1
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- name: Query dependencies
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run: |
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install.packages('remotes')
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saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2)
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writeLines(sprintf("R-%i.%i", getRversion()$major, getRversion()$minor), ".github/R-version")
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shell: Rscript {0}
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- name: Cache R packages
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uses: actions/cache@v2
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with:
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path: ${{ env.R_LIBS_USER }}
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key: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-${{ hashFiles('.github/depends.Rds') }}
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restore-keys: ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1-
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- name: Install system dependencies
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run: |
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while read -r cmd
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do
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eval sudo $cmd
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done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "20.04"))')
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- name: Install dependencies
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run: |
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remotes::install_deps(dependencies = TRUE)
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shell: Rscript {0}
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- name: Build package
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run: |
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R CMD build .
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- uses: actions/upload-artifact@v2
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with:
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name: DoubleML-pkg
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path: DoubleML_*.tar.gz

‎DESCRIPTION‎

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Package: DoubleML
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Type: Package
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Title: Double Machine Learning
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Version: 0.0.1
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Title: Double Machine Learning in R
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Version: 0.0.2
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Authors@R: c(
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person("Philipp", "Bach", email = "philipp.bach@uni-hamburg.de", role="aut"),
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person("Victor", "Chernozhukov", role="aut"),

‎R/double_ml.R‎

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checkmate::assert_count(n_rep_boot, positive = TRUE)
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private$initialize_boot_arrays(n_rep_boot)
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for (i_rep in 1:self$n_rep) {
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private$i_rep = i_rep
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if (self$apply_cross_fitting) {
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n_obs = self$data$n_obs
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} else {
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smpls = private$get__smpls()
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test_ids = smpls$test_ids
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test_index = test_ids[[1]]
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n_obs = length(test_index)
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}
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weights = draw_weights(method, n_rep_boot, n_obs)
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for (i_treat in 1:self$data$n_treat) {
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private$i_treat = i_treat
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boot_res = private$compute_bootstrap(method, n_rep_boot)
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boot_res = private$compute_bootstrap(weights, n_rep_boot)
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boot_coef = boot_res$boot_coef
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boot_t_stat = boot_res$boot_t_stat
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private$set__boot_coef(boot_coef)
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#' A nested `list()`. The outer lists needs to provide an entry per repeated sample splitting (length of the list is set as `n_rep`). The inner list is a named `list()` with names `train_ids` and `test_ids`. The entries in `train_ids` and `test_ids` must be partitions per fold (length of `train_ids` and `test_ids` is set as `n_folds`).
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#'
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#' @return self
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set_samples = function(smpls) {
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set_sample_splitting = function(smpls) {
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checkmate::assert_list(smpls)
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self$n_rep = length(smpls)
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n_folds_each_train_smpl = vapply(smpls, function(x) length(x$train_ids), integer(1L))
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invisible(self)
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},
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compute_bootstrap = function(method, n_rep_boot) {
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compute_bootstrap = function(weights, n_rep_boot) {
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dml_procedure = self$dml_procedure
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smpls = private$get__smpls()
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test_ids = smpls$test_ids
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n_obs = length(test_index)
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}
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if (method == "Bayes") {
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weights = stats::rexp(n_rep_boot * n_obs, rate = 1) - 1
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} else if (method == "normal") {
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weights = stats::rnorm(n_rep_boot * n_obs)
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} else if (method == "wild") {
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weights = stats::rnorm(n_rep_boot * n_obs)/sqrt(2) + (stats::rnorm(n_rep_boot * n_obs)^2 - 1)/2
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} else {
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stop("invalid boot method")
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}
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# for alignment with the functional (loop-wise) implementation we fill by row
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weights = matrix(weights, nrow = n_rep_boot, ncol = n_obs, byrow=TRUE)
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if (self$apply_cross_fitting) {
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if (dml_procedure == "dml1") {
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boot_coefs = boot_t_stat = matrix(NA, nrow = n_rep_boot, ncol = self$n_folds)

‎R/helper.R‎

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}
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# helper to draw weights in multiplier bootstrap
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draw_weights = function(method, n_rep_boot, n_obs) {
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if (method == "Bayes") {
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weights = stats::rexp(n_rep_boot * n_obs, rate = 1) - 1
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} else if (method == "normal") {
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weights = stats::rnorm(n_rep_boot * n_obs)
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} else if (method == "wild") {
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weights = stats::rnorm(n_rep_boot * n_obs)/sqrt(2) + (stats::rnorm(n_rep_boot * n_obs)^2 - 1)/2
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} else {
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stop("invalid boot method")
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}
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weights = matrix(weights, nrow = n_rep_boot, ncol = n_obs, byrow=TRUE)
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return(weights)
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}
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format.perc = function (probs, digits) {
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paste(format(100 * probs, trim = TRUE, scientific = FALSE, digits = digits),
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"%" ) }

‎README.Rmd‎

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<!-- README.md is generated from README.Rmd. Please edit that file -->
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# DoubleML - Double Machine Learning in python and R
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# DoubleML - Double Machine Learning in R
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The R package **DoubleML** provides an implementation of the double / debiased machine learning framework of [Chernozhukov et al. (2018)](https://arxiv.org/abs/1608.00060). It is built on top of [mlr3](https://mlr3.mlr-org.com/) and the [mlr3 ecosystem](https://github.com/mlr-org/mlr3/wiki/Extension-Packages) (Lang et al., 2019).
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* ... alternative resampling schemes,
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* ...
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![OOP structure of the DoubleML package](man/figures/oop.svg?raw=true)
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## Installation
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**DoubleML** requires
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```
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## Citation
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If you use the DoubleML package a citation is highly appreciated:
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Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M. (2020),
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DoubleML - Double Machine Learning in R.
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URL: [https://github.com/DoubleML/doubleml-for-r](https://github.com/DoubleML/doubleml-for-r),
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R-Package version 0.1.0.
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Bibtex-entry:
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```
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@Manual{DoubleML2020,
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title = {DoubleML - Double Machine Learning in R},
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author = {Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M.},
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year = {2020},
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note = {URL: \url{https://github.com/DoubleML/doubleml-for-r}, R-Package version 0.1.0}
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}
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```
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## References
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* Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W. and Robins, J. (2018), Double/debiased machine learning for treatment and structural parameters. The Econometrics Journal, 21: C1-C68. [doi:10.1111/ectj.12097](doi:10.1111/ectj.12097).

‎README.md‎

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<!-- README.md is generated from README.Rmd. Please edit that file -->
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# DoubleML - Double Machine Learning in python and R
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# DoubleML - Double Machine Learning in R
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The R package **DoubleML** provides an implementation of the double /
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debiased machine learning framework of [Chernozhukov et
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- … alternative resampling schemes,
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- …
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![OOP structure of the DoubleML package](man/figures/oop.svg?raw=true)
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## Installation
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**DoubleML** requires
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remotes::install_github("DoubleML/doubleml-for-r")
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```
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## Citation
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If you use the DoubleML package a citation is highly appreciated:
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Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M. (2020),
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DoubleML - Double Machine Learning in R. URL:
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<https://github.com/DoubleML/doubleml-for-r>, R-Package version 0.1.0.
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Bibtex-entry:
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@Manual{DoubleML2020,
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title = {DoubleML - Double Machine Learning in R},
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author = {Bach, P., Chernozhukov, V., Kurz, M. S., and Spindler, M.},
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year = {2020},
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note = {URL: \url{https://github.com/DoubleML/doubleml-for-r}, R-Package version 0.1.0}
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}
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## References
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- Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen,

‎man/DoubleML.Rd‎

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‎man/DoubleMLIIVM.Rd‎

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