Description Usage Details Author(s) References

Internal BeSS functions

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
bess.lm(x, y, beta0, s, max.steps=20, factor = NULL,
weights=rep(1,nrow(x)), normalize=FALSE)
bess.glm(x, y, beta0, intercept=0, s, max.steps=20,
glm.max=1e6, factor = NULL,
weights=rep(1,nrow(x)), normalize=FALSE)
bess.cox(x, y, beta0, s, cox.max=20, max.steps=20, factor=NULL,
weights=rep(1,nrow(x)), normalize=FALSE)
gbess.lm(x, y, Gi, beta0, s, max.steps = 20,
weights=rep(1,nrow(x)), normalize=FALSE)
gbess.glm(x, y, Gi, beta0, intercept=0, s, max.steps = 10, glm.max=1e6,
weights=rep(1,nrow(x)), normalize=FALSE)
gbess.cox(x, y, Gi, beta0, s, cox.max=20, max.steps=10,
weights=rep(1,nrow(x)), normalize=FALSE)
``` |

These are not intended for use by users. `bess.lm`

fit a linear regression model. `bess.glm`

fit a logistic model. `bess.cox`

fit a cox model.

Canhong Wen, Aijun Zhang, Shijie Quan, and Xueqin Wang.

Wen, C., Zhang, A., Quan, S. and Wang, X. (2017). BeSS: an R package for best subset selection in linear, logistic and CoxPH models. arXiv: 1709.06254.

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