penalized - L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation in GLMs and in the Cox Model

Fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.

Last updated 3 years ago

openblascpp

7.09 score 4 stars 17 dependents 429 scripts 2.8k downloads

globaltest - Testing Groups of Covariates/Features for Association with a Response Variable, with Applications to Gene Set Testing

The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.

Last updated 4 months ago

microarrayonechannelbioinformaticsdifferentialexpressiongopathways

6.96 score 7 dependents 79 scripts 2.8k downloads

cherry - Multiple Testing Methods for Exploratory Research

Provides an alternative approach to multiple testing by calculating a simultaneous upper confidence bounds for the number of true null hypotheses among any subset of the hypotheses of interest, using the methods of Goeman and Solari (2011) <doi:10.1214/11-STS356>.

Last updated 2 months ago

3.54 score 4 dependents 29 scripts 750 downloads

hommel - Methods for Closed Testing with Simes Inequality, in Particular Hommel's Method

Provides methods for closed testing using Simes local tests. In particular, calculates adjusted p-values for Hommel's multiple testing method, and provides lower confidence bounds for true discovery proportions. A robust but more conservative variant of the closed testing procedure that does not require the assumption of Simes inequality is also implemented. The methods have been described in detail in Goeman et al (Biometrika 106, 841-856, 2019).

Last updated 2 months ago

cpp

2.92 score 1 stars 11 dependents 25 scripts 924 downloads