Description: This package provides feature selection SVM using penalty
SCAD' (SCAD and 'L2-norm') penalties are availible. The tuning
parameters can be founf using either a fixed grid or a interval

Title: Integrative Penalized Conditional Logistic Regression
Description: Implements L1 and L2 penalized conditional logistic regression with penalty
factors allowing for integration of multiple data sources. Implements
stability selection for variable selection.
Imports: penalized, survival, clogitL1, stats, tidyverse
Author: Vera Djordjilovi'c [aut, cre] (<https://orcid.org/0000-0002-7670-3111>),

Description: Implementations of algorithms from
Learning Sparse Penalties for Change-point Detection
using Max Margin Interval Regression, by
Suggests: Segmentor3IsBack, neuroblastoma, microbenchmark, cghseg,
testthat, future, directlabels (>= 2017.03.31)

Suggests: Segmentor3IsBack, neuroblastoma, microbenchmark, testthat,

future, future.apply, directlabels (>= 2017.03.31)

Imports: data.table (>= 1.9.8), geometry, ggplot2

Suggests: neuroblastoma, jointseg, testthat, future, future.apply,

Title: Penalized Regression Calibration (PRC)
Description: Computes the penalized regression calibration (PRC)
method, that allows to predict survival using high-dimensional
longitudinal predictors. PRC is described in Signorelli et al.  (in
Imports: foreach, doParallel, glmnet, nlme, survival, MASS, survcomp,
Packaged: 2020-11-23 13:48:50 UTC; msignorelli

Imports: foreach, doParallel, glmnet, nlme, survival, MASS, stats,
Packaged: 2020-12-03 10:41:24 UTC; msignorelli

Packaged: 2021-01-05 08:46:45 UTC; msignorelli

Suggests: ptmixed, survminer, knitr, rmarkdown
Packaged: 2021-01-15 09:20:41 UTC; msignorelli

Description: Computes penalized regression calibration (PRC), a
statistical method that allows to predict survival from
high-dimensional longitudinal predictors. PRC is described in
Signorelli et al.  (in review, arXiv preprint: <arXiv:2101.04426>)).
survcomp, survivalROC, dplyr, Matrix, magic, lcmm
Packaged: 2021-03-16 16:36:06 UTC; msignorelli