Regularized CRM

Description

Fit a 2-parameter CRM model (O'Quigley and Shen 1996) regularized with L2 norm (Friedman et al. 2010) adjusted by the distance with the target DLT rate.

The package uses one-step coordinate descent algorithm and runs extremely fast.

Details

Functions: rCRM

Author(s)

Xiang Li, Hong Tian, Kevin Liu, Pilar Lim
Maintainer: Xiang Li <xli256@its.jnj.com>

References

O'Quigley, J., Shen, L.Z. (1996). Continual reassessment method: a likelihood approach. Biometrics, pp.673-684.
Friedman, J., Hastie, T. and Tibshirani, R. (2010). Regularization paths for generalized linear models via coordinate descent, Journal of Statistical Software, Vol. 33(1), 1.

Examples

set.seed(1213)

dose0=c(1:6)
prob0=c(0.007, 0.086, 0.294, 0.545, 0.731, 0.841)

m=3; Y=NULL; X=NULL
for (i in 1:length(dose0)) {
  Y=c(Y, rbinom(m, size=1, prob=prob0[i]))
  X=c(X, rep(i, m))
}

fiti=rCRM(X, Y, dose0, tp=0.3, mlambda=10)
# attributes(fiti)