Package: deli 0.1.0

Malcolm Barrett

deli: M-Estimation and Empirical Sandwich Variance Estimation

Solves estimating equations to obtain M-estimators together with empirical sandwich variance estimates, providing a general interface for both custom and built-in estimating equations. Built-in equations cover basic statistics, regression, causal inference, survival analysis, measurement error, and more. An 'R' port of the 'Python' library 'delicatessen' described in 'Zivich et al. (2022)' <doi:10.48550/arXiv.2203.11300>.

Authors:Malcolm Barrett [aut, cre, cph], Paul Zivich [ctb]

deli_0.1.0.tar.gz
deli_0.1.0.zip(r-4.7-any)deli_0.1.0.zip(r-4.6-any)deli_0.1.0.zip(r-4.5-any)
deli_0.1.0.tgz(r-4.6-any)deli_0.1.0.tgz(r-4.5-any)
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deli_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
deli/json (API)

# Install 'deli' in R:
install.packages('deli', repos = c('https://r-causal.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/r-causal/deli/issues

Pkgdown/docs site:https://r-causal.github.io

Datasets:

On CRAN:

Conda:

6.77 score 2 stars 4 packages 31 scripts 367 downloads 70 exports 5 dependencies

Last updated from:d3b0767bd2. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK194
source / vignettesOK207
linux-releaseOK168
macos-releaseOK193
macos-oldrelOK160
windows-develOK187
windows-releaseOK175
windows-oldrelOK182
wasm-releaseOK89

Exports:additive_design_matrixaft_predictions_functionaft_predictions_individualaggregate_efuncsaugmentcompute_confidence_bandscompute_sandwichconfidence_bandsconfidence_intervalsconvert_survival_measuresdeli_digammadeli_polygammadeli_splinedelta_methodee_2slsee_additive_regressionee_aftee_aipwee_beta_regressionee_bridge_regressionee_dlasso_regressionee_elasticnet_regressionee_emaxee_emax_edee_gestimation_snmmee_gformulaee_glmee_ipwee_ipw_msmee_iv_causalee_lasso_regressionee_loglogisticee_loglogistic_edee_meanee_mean_geometricee_mean_robustee_mean_sensitivity_analysisee_mean_varianceee_mlogitee_percentileee_plogitee_positive_mean_deviationee_regressionee_regression_calibrationee_ridge_regressionee_robust_regressionee_rogan_gladenee_rogan_gladen_extendedee_survival_modelee_tobitestimateglancegmm_estimateGMMEstimatoridentity_transforminfluence_functionsinverse_logitlogitm_estimateMEstimatorp_valuesplogit_predictregression_predictionsrobust_loss_functionss_valuesstandard_normal_cdfstandard_normal_pdfsurvival_predictionstidyz_scores

Dependencies:cligenericsrlangrootSolveS7

Getting Started with deli
Overview | Fitting your first model | Inspecting the fit | Other regression models | The estimator objects | Stacking estimating equations | Causal inference: inverse probability weighting | Predictions | Clustered data | Exact differentiation | Next steps
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-08-03
Started: 2026-07-16

Regression Models
Overview | Linear regression | Logistic regression | Poisson regression | GLM: generalized linear models | Penalized regression | Ridge regression | LASSO regression | Elastic net | Robust regression | Weighted regression | Predictions after regression
Rendered fromregression-models.Rmdusingknitr::rmarkdown

Last update: 2026-08-03
Started: 2026-07-16

Causal Inference
Overview | Simulated data | G-formula (g-computation) | Inverse probability weighting (IPW) | Truncating propensity scores | Augmented IPW (doubly robust) | Comparing methods | Further reading
Rendered fromcausal-inference.Rmdusingknitr::rmarkdown

Last update: 2026-08-02
Started: 2026-07-16

Custom Estimating Equations
Overview | Writing a custom estimating equation | Example: estimating a ratio of means | Key points for custom equations | Stacking custom EEs with built-in ones | Example: log odds-ratio from logistic regression | How stacking works | Using the delta method | Example: odds ratio via the delta method | When to use the delta method vs. stacking | Using the delta method with raw estimates
Rendered fromcustom-estimating-equations.Rmdusingknitr::rmarkdown

Last update: 2026-07-29
Started: 2026-07-16

Readme and manuals

Help Manual

Help pageTopics
ACTG 175 clinical trial dataactg175
Build an additive design matrix for GAMsadditive_design_matrix
Function-level predicted survival measures from an AFT modelaft_predictions_function
Predicted survival measures from an AFT modelaft_predictions_individual
Aggregate estimating function contributions by groupaggregate_efuncs
Bonate adverse events databonate_adverse
Breast cancer survival databreast_cancer
Collett bladder cancer recurrence datacollett_bladder
Compute confidence bands from theta and covariancecompute_confidence_bands
Compute the empirical sandwich variance estimatorcompute_sandwich
Confidence bands for parameter vectorsconfidence_bands
Confidence intervals for M-Estimator parametersconfidence_intervals
Convert between survival analysis measuresconvert_survival_measures
US state crime datacrime
Cutler (1995) pharmacodynamic datacutler1995
Digamma functiondeli_digamma
Polygamma functiondeli_polygamma
Generate polynomial spline basis termsdeli_spline
Augment data with predictions from a fitted deli estimatoraugment.deli::deli_estimator deli-augment
The condition classes deli raisesdeli-conditions
Display methods for deli estimatorsdeli-display print.deli::deli_estimator summary.deli::deli_estimator
Standard S3 generics for deli estimatorscoef.deli::deli_estimator confint.deli::deli_estimator deli-generics deviance.deli::deli_estimator df.residual.deli::deli_estimator fitted.deli::deli_estimator formula.deli::deli_estimator logLik.deli::deli_estimator model.frame.deli::deli_estimator model.matrix.deli::deli_estimator nobs.deli::deli_estimator residuals.deli::deli_estimator sigma.deli::deli_estimator terms.deli::deli_estimator vcov.deli::deli_estimator weights.deli::deli_estimator
Predictions from a fitted deli estimatordeli-predict predict.deli::deli_estimator
Broom tidiers for deli estimatorsdeli-tidiers glance.deli::deli_estimator tidy.deli::deli_estimator
Delta method for variance of transformed parametersdelta_method
Estimating equations for Two-Stage Least Squares (2SLS)ee_2sls
Estimating equation for additive regression (GAM)ee_additive_regression
Estimating equation for accelerated failure time modelsee_aft
Estimating equations for augmented inverse probability weighting (AIPW)ee_aipw
Estimating equation for beta regressionee_beta_regression
Estimating equation for bridge penalized regressionee_bridge_regression
Estimating equation for differentiable LASSO regressionee_dlasso_regression
Estimating equation for elastic net regressionee_elasticnet_regression
Estimating equation for E-max dose-response modelee_emax
Estimating equation for delta-effective dose (E-max)ee_emax_ed
Estimating equations for g-estimation of structural nested mean modelsee_gestimation_snmm
Estimating equations for the g-formula (g-computation)ee_gformula
Estimating equation for generalized linear modelsee_glm
Estimating equations for inverse probability weighting (IPW)ee_ipw
Estimating equations for IPW marginal structural modelee_ipw_msm
Estimating equations for instrumental variable (IV) estimationee_iv_causal
Estimating equation for approximate LASSO regressionee_lasso_regression
Estimating equation for 4-parameter log-logistic dose-response modelee_loglogistic
Estimating equation for delta-effective dose (log-logistic)ee_loglogistic_ed
Estimating equation for the meanee_mean
Estimating equation for the geometric meanee_mean_geometric
Estimating equation for the robust meanee_mean_robust
Estimating equations for weighted sensitivity analysis of the meanee_mean_sensitivity_analysis
Estimating equations for the mean and varianceee_mean_variance
Estimating equation for multinomial logistic regressionee_mlogit
Estimating equation for the percentileee_percentile
Estimating equation for pooled logistic regressionee_plogit
Estimating equations for the positive mean deviationee_positive_mean_deviation
Estimating equation for regressionee_regression
Estimating equation for regression calibrationee_regression_calibration
Estimating equation for ridge regressionee_ridge_regression
Estimating equation for robust regressionee_robust_regression
Estimating equation for Rogan-Gladen correctionee_rogan_gladen
Estimating equation for extended Rogan-Gladen correctionee_rogan_gladen_extended
Estimating equation for parametric survival modelsee_survival_model
Estimating equation for Tobit regression (Type I)ee_tobit
Estimate parameters and sandwich varianceestimate
GetTested randomized trial dataget_tested
One-step GMM estimationgmm_estimate gmm_estimate.default gmm_estimate.formula
GMM EstimatorGMMEstimator
Identity transformationidentity_transform
Inderjit dose-response datainderjit
Influence functions for M-Estimatorinfluence_functions
Inverse logistic transformationinverse_logit
Lau WIHS HIV/CD4 datalau_wihs
Logistic transformationlogit
One-step M-estimationm_estimate m_estimate.default m_estimate.formula
M-EstimatorMEstimator
Mroz labor force participation datamroz
NSDUH substance use survey datansduh
P-values for M-Estimator parametersp_values
Predicted survival measures from a pooled logistic regression modelplogit_predict
PPARg cheminformatics datapparg
Generate predicted values from a regression modelregression_predictions
Robust loss function derivativesrobust_loss_functions
Robust regression example datarobust_regress
S-values (surprisal) for M-Estimator parameterss_values
SDSS quasar survey datasdss_quasar
Shaquille O'Neal free throw datashaq_free_throws
Standard normal CDFstandard_normal_cdf
Standard normal PDFstandard_normal_pdf
Generate predicted survival measures from a parametric survival modelsurvival_predictions
Z-scores for M-Estimator parametersz_scores