rbsurv                package:rbsurv                R Documentation

_R_o_b_u_s_t _l_i_k_e_l_i_h_o_o_d-_b_a_s_e_d _s_u_r_v_i_v_a_l _m_o_d_e_l_i_n_g

_D_e_s_c_r_i_p_t_i_o_n:

     This selects survival-associated genes with microarray data.

_U_s_a_g_e:

             rbsurv(time, ...)

_A_r_g_u_m_e_n_t_s:

    time: an object for which the extraction of model rbsurv is
          meaningful.

     ...: other arguments

_A_u_t_h_o_r(_s):

     HyungJun Cho, Sukwoo Kim, Soo-heang Eo, and Jaewoo Kang

_R_e_f_e_r_e_n_c_e_s:

     Cho,H., Yu,A., Kim,S., Kang,J., and Hong S-M. (2009).  Robust
     likelihood-based survival modeling for microarray gene expression
     Data,  _Journal of Statistical Software_, 29(1):1-16. URL
     http://www.jstatsoft.org/v29/i01/.

_S_e_e _A_l_s_o:

     'rbsurv.default'

_E_x_a_m_p_l_e_s:

     library(rbsurv)
     data(gliomaSet)
     x <- exprs(gliomaSet)
     x <- log2(x)
     time <- gliomaSet$Time
     status <- gliomaSet$Status
     z <- cbind(gliomaSet$Age, gliomaSet$Gender) 

     fit <- rbsurv(time=time, status=status, x=x,  method="efron", max.n.genes=20, n.iter=10, n.fold=3,  n.seq=1)
     fit$model

