FHT: FHT data introduced in Simon et al. (2011).

In fastcox: Lasso and Elastic-Net Penalized Cox's Regression in High Dimensions Models using the Cocktail Algorithm

FHT data introduced in Simon et al. (2011).

Description

The FHT data set has n = 50 observations and p = 100 predictors. The covariance between predictors Xj and Xj' has the same correlation 0.5. See details in Simon et al. (2011).

Usage

data(FHT)

Format

This list object named "FHT" contains the following data:

x

a covariate matrix with 50 rows and 100 columns

y

the distinct failure times

status

the censoring indicator (status = 1 indicates no censoring and status = 0 indicates right censoring)

References

Friedman, J., Hastie, T. and Tibshirani, R. (2008) "Regularization Paths for Generalized Linear Models via Coordinate Descent", https://web.stanford.edu/~hastie/Papers/glmnet.pdf
Journal of Statistical Software, Vol. 33(1), 1-22 Feb 2010
https://www.jstatsoft.org/v33/i01/

Simon, N., Friedman, J., Hastie, T., Tibshirani, R. (2011) "Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent", Journal of Statistical Software, Vol. 39(5) 1-13
https://www.jstatsoft.org/v39/i05/

Examples

data(FHT)

fastcox documentation built on June 8, 2025, 10:47 a.m.