Man pages for gregorkb/aenetgt
Adaptive Elastic Net for Group Testing Data

aenetgt-packageAdaptive Elastic Net for Group Testing Data
aic.bic.eric.enetgt.gridChooses tuning parameters via AIC, BIC, and ERIC.
array.assay.genGenerates array testing data.
CovYiYj.approxApproximates the conditional covariance between all pairs of...
cv.enetgt.gridPeforms crossvalidation to select a combination of tuning...
dorfman.assay.genGenerates Dorfman testing data.
enetgtComputes the elastic net estimator with weighted l1 norm on...
enetgt.gridComputes the elastic net estimators with weighted l1 norm on...
EY.approxApproximates the conditional expectations of individual...
EY.exactComputes conditional expectations of individual disease...
get.array.cv.fold.dataSplits array testing data into crossvalidation data sets.
get.dorfman.cv.fold.dataSplits Dorfman testing data into crossvalidation data sets.
get.individual.cv.fold.dataSplits individual testing data into crossvalidation data...
get.masterpool.cv.fold.dataSplits masterpool testing data into crossvalidation data sets
individual.assay.genGenerates individual testing data.
logitCompute probabilities based on the logit link.
masterpool.assay.genGenerates master pool testing data.
mlegtComputes the mle on group testing data.
model0Generates data from model0.
model1Generates data from model1.
model2Generates data from model2.
model3Generates data from model3.
gregorkb/aenetgt documentation built on May 17, 2019, 11:07 a.m.