twilight.getlambda         package:twilight         R Documentation

_I_n_t_e_r_n_a_l _f_u_n_c_t_i_o_n _t_o _c_o_m_p_u_t_e _r_e_g_u_l_a_r_i_z_a_t_i_o_n _p_a_r_a_m_e_t_e_r _l_a_m_b_d_a

_D_e_s_c_r_i_p_t_i_o_n:

     The SEP method optionally includes a penalty term in order to
     estimate the percentage of non-significant differences/genes.

_U_s_a_g_e:

     twilight.getlambda(xin, verbose = TRUE)

_A_r_g_u_m_e_n_t_s:

     xin: A numerical vector containing p-values.

 verbose: Logical value for message printing.

_D_e_t_a_i_l_s:

     The function finds a suitable regularization parameter lambda. For
     a sequence of lambdas, the objective function of SEP is computed
     for subsamples of the p-value vector 'xin'. The final estimate is
     chosen based upon a Wilcoxon test comparison between objective
     function values of lambda=0 and each lambda>0. The penalized
     objective function should not differ a lot from the unpenalized
     one. Therefore, the highest lambda that leads to a non-significant
     difference in means is chosen. The Wilcoxon ranksum test p-values
     are Bonferroni-corrected.

_V_a_l_u_e:

     Returns numerical value.

_A_u_t_h_o_r(_s):

     Stefanie Scheid <URL: http://www.molgen.mpg.de/~scheid>

_R_e_f_e_r_e_n_c_e_s:

     Scheid S and Spang R (2004): A stochastic downhill search
     algorithm for estimating the local false discovery rate, _IEEE
     TCBB_ *1(3)*, 98-108.

_S_e_e _A_l_s_o:

     'twilight'

