Packages by Imad EL BADISY

CEACT — 0.5.0

Cost-Effectiveness Analysis Toolkit for Clinical Trials

basetable — 1.4.2

Fast and Memory-Efficient Base R Table Manipulation

densemlp — 0.7.1

Dense Neural Networks for Tabular Regression, Classification and Survival

fastgbm — 0.6.1

Fast Histogram Gradient Boosting for Regression, Classification, and Survival Analysis

funcml — 0.9.0

Functional Machine Learning Framework

functionals — 0.5.1

Functional Programming with Parallelism and Progress Tracking

mcstatsim — 0.5.1

Monte Carlo Statistical Simulation Tools Using a Functional Approach

mimar — 1.0.0

Compact Multiple Imputation, Assessment, and Reporting

missCforest — 0.0.8

Ensemble Conditional Trees for Missing Data Imputation

missknn — 1.1.2

Fast Masked K-Nearest Neighbor Imputation

nbsurv — 0.5.1

Conditional Naive Bayes Survival Modelling for Right-Censored Data

panglm — 1.1.4

Generalized Linear Models for Panel Data

phynotype — 0.6.2

Clustering and Consensus Meta-Clustering

rpsurv — 0.7.1

Fast Royston-Parmar Flexible Parametric Survival Models

survalis — 1.0.0

Interpretable Survival Machine Learning Framework

survdnn — 1.0.0

Deep Neural Networks for Survival Analysis with R 'torch'

testflow — 1.0.0

A Workflow for Statistical Testing and Interpretation

tvrmst — 0.0.6

Time-Varying Restricted Mean Survival Time from Survival Matrices

unsurv — 0.7.2

Unsupervised Clustering of Individualized Survival Curves