- Main
Software for prediction and estimation with applications to high-dimensional genomic and epidemiologic data
- Ritter, Stephan Johannes
- Advisor(s): Hubbard, Alan E.
Abstract
Three add-on packages for the R statistical programming environment (R Core Team, 2013) are described, with simulations demonstrating performance gains and applications to real data. Chapter 1 describes the relaxnet package, which extends the glmnet package with relaxation (as in the relaxed lasso of Meinshausen, 2007). Chapter 2 describes the widenet package, which extends relaxnet with polynomial basis expansions. Chapter 3 describes the multiPIM package, which takes a causal inference approach to variable importance analysis. Section 3.7 describes an analysis of data from the PRospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study (Rahbar et al., 2012; Hubbard et al., 2013), for which the multiPIM package is used in conjunction with the relaxnet and widenet packages to estimate variable importances.
Main Content
Enter the password to open this PDF file:
-
-
-
-
-
-
-
-
-
-
-
-
-
-