Constructing multivariate survival trees

The MST package for R

Peter Calhoun, Xiaogang Su, Martha E. Nunn, Juanjuan Fan

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Multivariate survival trees require few statistical assumptions, are easy to interpret, and provide meaningful diagnosis and prediction rules. Trees can handle a large number of predictors with mixed types and do not require predictor variable transformation or selection. These are useful features in many application fields and are often required in the current era of big data. The aim of this article is to introduce the R package MST. This package constructs multivariate survival trees using marginal model and frailty model based approaches. It allows the user to control and see how the trees are constructed. The package can also simulate high-dimensional, multivariate survival data from marginal and frailty models.

Original languageEnglish (US)
JournalJournal of Statistical Software
Volume83
DOIs
StatePublished - Jan 1 2018

Fingerprint

Minimum Spanning Tree
Marginal Model
Frailty Model
Predictors
Multivariate Survival Data
Variable Transformation
Variable Selection
High-dimensional
Model-based
Minimum spanning tree
Prediction
Frailty

All Science Journal Classification (ASJC) codes

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Constructing multivariate survival trees : The MST package for R. / Calhoun, Peter; Su, Xiaogang; Nunn, Martha E.; Fan, Juanjuan.

In: Journal of Statistical Software, Vol. 83, 01.01.2018.

Research output: Contribution to journalArticle

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