Poisson Super Learner

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Documentation for package ‘poissonsuperlearner’ version 0.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

coef.base_learner	Extract coefficients from a fitted base learner
coef.poisson_superlearner	Extract stacking (meta-learner) coefficients from a fitted Poisson Super Learner
fit_learner	Fit a single base learner
Learner_gam	GAM learner via 'mgcv::bam'
Learner_gam-class	GAM learner via 'mgcv::bam'
Learner_glmnet	Penalized Poisson learner via 'glmnet'
Learner_glmnet-class	Penalized Poisson learner via 'glmnet'
Learner_hal	HAL learner for piecewise Poisson hazards
Learner_hal-class	HAL learner for piecewise Poisson hazards
pch_absolute_risk	Absolute risk (cumulative incidence) for a cause under piecewise-constant hazards
pch_absolute_risk_euler	Absolute risk (Euler approximation) for a cause under piecewise-constant hazards
pch_survival	Piecewise-constant hazards survival function
predict.base_learner	Predict hazards, survival and absolute risk from a fitted base learner
predict.poisson_superlearner	Predict hazards, survival and absolute risk from a fitted Poisson Super Learner
predictRisk.base_learner	Absolute-risk matrix predictions for a fitted base learner
predictRisk.poisson_superlearner	Absolute-risk matrix predictions for a fitted Poisson Super Learner
print.base_learner	Print method for 'base_learner'
print.poisson_superlearner	Print method for 'poisson_superlearner'
simulateStenoT1	Simulate time-to-event data for hypothetical type-1 diabetes patients
summary.base_learner	Summarize a fitted base learner object
summary.poisson_superlearner	Summarize a fitted Poisson Super Learner object
Superlearner	Fit a Poisson Super Learner ensemble