{ "_id": "6aa98fb5ea78b3e62eac7f7b", "Package": "ardldml", "Type": "Package", "Title": "Bounds Testing for Cointegration with Many Persistent Controls", "Version": "0.1.0", "Authors@R": "person(\"Merwan\", \"Roudane\",\nemail = \"merwanroudane920@gmail.com\",\nrole = c(\"aut\", \"cre\", \"cph\"))", "Description": "An implementation of the DML-Bounds procedure of Villena\n(2026) for testing cointegration in\ndata-rich time-series settings. The Autoregressive Distributed\nLag (ARDL) bounds test of Pesaran, Shin and Smith (2001)\n avoids pretesting the integration order\nof the regressors but is not designed for a high-dimensional\nconditioning set. Residualising the lagged levels against\npersistent controls can absorb stochastic trends and thereby\nchange the finite-sample null distribution, so what governs the\nnull is the effective number of stochastic trends surviving\nresidualisation rather than the integration order of the\noriginal regressors. The procedure combines h-block\ncross-fitting, a balanced nuisance projection in the Double\nMachine Learning (DML) style of Chernozhukov and others (2018)\n, adaptive weighting after Zou (2006)\n, and a restricted system wild\nbootstrap that regenerates the dependent variable and the focal\nregressor jointly. No critical-value table is shipped: the\nclassical bracket is regenerated by simulation and the\noperational critical value is bootstrapped. A trend-absorption\ndiagnostic and a penalty-sensitivity sweep report whether a\nverdict survives a change of conditioning set. Monthly United\nStates macroeconomic series from the 'FRED-MD' database of\nMcCracken and Ng (2016) are\nbundled so every example runs offline.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Language": "en-GB", "VignetteBuilder": "knitr", "LazyData": "true", "RoxygenNote": "7.3.3", "URL": "https://github.com/merwanroudane/ardldml", "BugReports": "https://github.com/merwanroudane/ardldml/issues", "Config/testthat/edition": "3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-15 18:31:37 UTC", "User": "root" }, "Author": "Merwan Roudane [aut, cre, cph]", "Maintainer": "Merwan Roudane ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-09-15 12:20:09 UTC", "RemoteUrl": "https://github.com/cran/ardldml", "RemoteRef": "HEAD", "RemoteSha": "96545b448e1ff181ce549ff8220ca89e80e631fa", "_user": "cran", "_type": "src", "_file": "ardldml_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/e3b7a79184c0c5c3148b1bbfa4ccdb53e29fd6fe3a0c697c56d4a7e8af942d72", 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"ardl_colors" ] }, { "page": "bounds_verdict", "title": "Mark a Statistic Against a Pair of Bounds", "topics": [ "bounds_verdict" ] }, { "page": "build_balanced_design", "title": "Build the Balanced First-Stage Design", "topics": [ "build_balanced_design", "print.ardl_design" ] }, { "page": "CASE_LABELS", "title": "Deterministic Case Labels", "topics": [ "CASE_LABELS" ] }, { "page": "classical_bounds_test", "title": "The Classical Bounds Test", "topics": [ "classical_bounds_test" ] }, { "page": "classify_controls", "title": "Split the Control Set into Stationary and Integrated Blocks", "topics": [ "classify_controls" ] }, { "page": "compute_statistic", "title": "Build the Design, Cross-Fit, Residualise and Test", "topics": [ "compute_statistic" ] }, { "page": "conditional_ecm", "title": "Fit the Unrestricted Conditional Error Correction Model", "topics": [ "conditional_ecm" ] }, { "page": "CONTROLS", "title": "The Seven Controls of the Full Conditioning Set", "topics": [ "CONTROLS" ] }, { "page": "cross_fit_projection", "title": "Cross-Fitted Projection", "topics": [ "cross_fit_projection" ] }, { "page": "decision", "title": "Verdict of a Fitted Test", "topics": [ "decision" ] }, { "page": "DEFAULT_INTEGRATED", "title": "Controls Treated as Integrated of Order One", "topics": [ "DEFAULT_INTEGRATED" ] }, { "page": "DEFAULT_LEVELS", "title": "Significance Levels Reported by Default", "topics": [ "DEFAULT_LEVELS" ] }, { "page": "dml_bootstrap", "title": "The Restricted System Wild Bootstrap", "topics": [ "dml_bootstrap" ] }, { "page": "dml_bounds", "title": "Test for a Long-Run Relationship with Many Persistent Controls", "topics": [ "dml_bounds", "print.dml_bounds", "summary.dml_bounds" ] }, { "page": "dml_spec", "title": "Specification of a DML-Bounds Fit", "topics": [ "dml_spec", "print.dml_spec" ] }, { "page": "hblock_folds", "title": "h-Block Cross-Fitting Folds", "topics": [ "as.data.frame.ardl_folds", "hblock_folds", "print.ardl_folds" ] }, { "page": "k_convention_offset", "title": "The k-Convention Offset", "topics": [ "k_convention_offset" ] }, { "page": "LOG_SERIES", "title": "Series Transformed to Logs", "topics": [ "LOG_SERIES" ] }, { "page": "n_restrictions", "title": "Number of Restrictions in the Bounds Test", "topics": [ "n_restrictions" ] }, { "page": "parula_colors", "title": "MATLAB Parula Color Palette", "topics": [ "parula_colors" ] }, { "page": "passthrough", "title": "Exchange-Rate Pass-Through Data", "topics": [ "passthrough" ] }, { "page": "passthrough_regime", "title": "Load a Regime of the Pass-Through Data", "topics": [ "passthrough_regime" ] }, { "page": "PASSTHROUGH_REGIMES", "title": "The Four Monetary Regimes", "topics": [ "PASSTHROUGH_REGIMES" ] }, { "page": "PENALTY_RULES", "title": "Penalty Rules of the Robustness Grid", "topics": [ "PENALTY_RULES" ] }, { "page": "penalty_sensitivity", "title": "Sweep the Penalty and the Projection", "topics": [ "penalty_sensitivity" ] }, { "page": "plot_bracket", "title": "Plot the Trend-Absorption Bracket", "topics": [ "plot_bracket" ] }, { "page": "plot.dml_bounds", "title": "Plot the Simulated Null of a Fitted Test", "topics": [ "plot.dml_bounds" ] }, { "page": "plugin_penalty", "title": "The Plug-In Penalty", "topics": [ "plugin_penalty" ] }, { "page": "print.classical_bounds", "title": "Print a Classical Bounds Test", "topics": [ "print.classical_bounds" ] }, { "page": "pss_reference", "title": "Published Bounds for a Validated Cell", "topics": [ "pss_reference" ] }, { "page": "rademacher", "title": "Rademacher Weights", "topics": [ "rademacher" ] }, { "page": "REDUCED_DROP", "title": "Controls Dropped to Form the Reduced Set", "topics": [ "REDUCED_DROP" ] }, { "page": "sample_use", "title": "Share of the Sample Available for Training", "topics": [ "sample_use" ] }, { "page": "sample_use_table", "title": "Training Share Across a Grid of K and h", "topics": [ "sample_use_table" ] }, { "page": "simulate_pss_bounds", "title": "Generate the Classical Bounds by Simulation", "topics": [ "simulate_pss_bounds" ] }, { "page": "trend_absorption", "title": "The Trend-Absorption Diagnostic", "topics": [ "absorption_verdict", "as.data.frame.trend_absorption", "print.trend_absorption", "trend_absorption" ] }, { "page": "tscv_penalty", "title": "Rolling-Origin Cross-Validation for the Penalty", "topics": [ "tscv_penalty" ] } ], "_rundeps": [ "codetools", "foreach", "glmnet", "iterators", "lattice", "Matrix", "Rcpp", "RcppEigen", "shape", "survival" ], "_vignettes": [ { "source": "ardldml.Rmd", "filename": "ardldml.html", "title": "Bounds testing when the controls carry trends", "author": "Dr Merwan Roudane", "engine": "knitr::rmarkdown", "headings": [ "What this package is for", "The second unknown", "Why no bounds table ships with this package", "The data", "A first fit", "The diagnostic you must run", "Penalty sensitivity", "Where the critical values come from", "Validation", "Limitations", "References" ], "created": "2026-09-15 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