SuperLearner: Super Learner Prediction

Canonical link: https://scholar.rpkg.net/pkg/SuperLearner

Eric Polley • Erin LeDell • Chris Kennedy • Sam Lendle • Mark van der Laan • View description and downloads View dependencies GitHub project

2011 Published

2.0-29 Version

0 Citations

5 Authors

Referenced by ⇅	Year
survtmle: Compute Targeted Minimum Loss-Based Estimates in Right-Censored Survival Settings (Version 1.1.1)	2017
concrete: Continuous-Time Competing Risks Estimation using Targeted Minimum Loss-Based Estimation (TMLE) (Version 1.0.5)	2023
AIPW: Augmented Inverse Probability Weighting (Version 0.6.3.2)	2021
CIMTx: Causal Inference for Multiple Treatments with a Binary Outcome (Version 1.2.0)	2020
CRE: Interpretable Discovery and Inference of Heterogeneous Treatment Effects (Version 0.2.5)	2022
CausalGPS: Matching on Generalized Propensity Scores with Continuous Exposures (Version 0.4.2)	2021
CausalMetaR: Causally Interpretable Meta-Analysis (Version 0.1.1)	2024
DRDRtest: A Nonparametric Doubly Robust Test for Continuous Treatment Effect (Version 0.1)	2021
EScvtmle: Experiment-Selector CV-TMLE for Integration of Observational and RCT Data (Version 0.0.2)	2022
GPCERF: Gaussian Processes for Estimating Causal Exposure Response Curves (Version 0.2.4)	2022
PSweight: Propensity Score Weighting for Causal Inference with Observational Studies and Randomized Trials (Version 1.2.0)	2020
RISCA: Causal Inference and Prediction in Cohort-Based Analyses (Version 1.0.5)	2020
Ricrt: Randomization Inference of Clustered Randomized Trials (Version 0.1.0)	2023
RobinCar: Robust Estimation and Inference in Covariate-Adaptive Randomization (Version 0.2.0)	2024
WeightIt: Weighting for Covariate Balance in Observational Studies (Version 1.0.0)	2017
amp: Statistical Test for the Multivariate Point Null Hypotheses (Version 1.0.0)	2022
causalweight: Estimation Methods for Causal Inference Based on Inverse Probability Weighting (Version 1.1.0)	2018
crossurr: Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers (Version 1.0.6)	2022
ctmle: Collaborative Targeted Maximum Likelihood Estimation (Version 0.1.2)	2017
drpop: Efficient and Doubly Robust Population Size Estimation (Version 0.0.3)	2021
drtmle: Doubly-Robust Nonparametric Estimation and Inference (Version 1.1.2)	2017
evalITR: Evaluating Individualized Treatment Rules (Version 1.0.0)	2020
flevr: Flexible, Ensemble-Based Variable Selection with Potentially Missing Data (Version 0.0.4)	2023
gKRLS: Generalized Kernel Regularized Least Squares (Version 1.0.2)	2023
hal9001: The Scalable Highly Adaptive Lasso (Version 0.4.6)	2020
lmtp: Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies (Version 1.3.3)	2020
ltmle: Longitudinal Targeted Maximum Likelihood Estimation (Version 1.3-0)	2015
medflex: Flexible Mediation Analysis Using Natural Effect Models (Version 0.6-10)	2014
nestedcv: Nested Cross-Validation with 'glmnet' and 'caret' (Version 0.7.8)	2022
nlpred: Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples (Version 1.0.1)	2019
polle: Policy Learning (Version 1.3)	2022
riskRegression: Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks (Version 2023.12.21)	2011
subsemble: An Ensemble Method for Combining Subset-Specific Algorithm Fits (Version 0.1.0)	2014
superMICE: SuperLearner Method for MICE (Version 1.1.1)	2022
survML: Flexible Estimation of Conditional Survival Functions Using Machine Learning (Version 1.1.0)	2023
targeted: Targeted Inference (Version 0.5)	2020
tehtuner: Fit and Tune Models to Detect Treatment Effect Heterogeneity (Version 0.3.0)	2022
tidyhte: Tidy Estimation of Heterogeneous Treatment Effects (Version 1.0.2)	2023
tmle: Targeted Maximum Likelihood Estimation (Version 2.0.0)	2012
vaccine: Statistical Tools for Immune Correlates Analysis of Vaccine Clinical Trial Data (Version 1.2.1)	2023
vglmer: Variational Inference for Hierarchical Generalized Linear Models (Version 1.0.3)	2022
vimp: Perform Inference on Algorithm-Agnostic Variable Importance (Version 2.3.3)	2018

RPKG Scholar presents a tabulation of an author's contribution in the development of R packages stored in the Comprehensive R Archive Network (CRAN). Within this site, we consider package dependencies (suggests,imports,depends,enhances) as citations because we believe that using one's package to develop another is tantamount to citing the author of the package being imported, suggested or enhanced.