# uniCox: Function to fit a high dimensional Cox survival model using... In uniCox: Univarate shrinkage prediction in the Cox model

## Description

Function to fit a high dimensional Cox survival model using Univariate Shrinkage

## Usage

 `1` ```uniCox(x,y,status,lamlist=NULL,nlam=20,del.thres=.01, max.iter=5) ```

## Arguments

 `x` Feature matrix, n obs by p variables `y` Vector of n survival times `status` Vector of n censoring indicators (1= died or event occurred,0=survived, or event was censored) `lamlist` Optional vector of lambda values for solution path `nlam` Number of lambda values to consider `del.thres` Convergence threshold `max.iter` Maximum number of iterations for each lambda

## Details

This function builds a prediction model for survival data with high-dimensional covariates, using the Unvariate Shringae method.

## Value

A list with components

 `lamlist` Values of lambda used `beta` Coef estimates, number of features by number of lambda values `mx` Mean of feature columns `vx` Square root of Fisher information for each feature `s0` Exchangeability factor for denominator of score statistic `call` Call to this function

## Source

Tibshirani, R. Univariate shrinkage in the Cox model for high dimensional data (2009). http://www-stat.stanford.edu/~tibs/ftp/cus.pdf To appear SAGMB.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31``` ```library(survival) # generate some data x=matrix(rnorm(200*1000),ncol=1000) y=abs(rnorm(200)) x[y>median(y),1:50]=x[y>median(y),1:50]+3 status=sample(c(0,1),size=200,replace=TRUE) xtest=matrix(rnorm(50*1000),ncol=1000) ytest=abs(rnorm(50)) xtest[ytest>median(ytest),1:50]=xtest[ytest>median(ytest),1:50]+3 statustest=sample(c(0,1),size=50,replace=TRUE) # fit uniCox model a=uniCox(x,y,status) # look at results print(a) # do cross-validation to examine choice of lambda aa=uniCoxCV(a,x,y,status) # look at results print(aa) # get predictions on a test set yhat=predict.uniCox(a,xtest) # fit survival model to predicted values coxph(Surv(ytest,statustest)~yhat[,7]) ```

uniCox documentation built on May 29, 2017, 2:19 p.m.