beams                 package:LMGene                 R Documentation

_B_e_a_m _s_e_a_r_c_h _r_o_u_n_t_i_n_e _f_o_r _f_i_n_d_i_n_g _t_h_e _o_p_t_i_m_a_l _p_a_r_a_m_e_t_e_r_s

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

     This routine finds optimal values of the two parameters, alpha and
     lambda, for the glog transformation function

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

     beams(eS, startvar)

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

      eS: Array data. must be a exprSet type  

startvar: Given (initial) value of log(alpha) and lambda 

_D_e_t_a_i_l_s:

     The input argument, eS, must be exprSet type from Biobase package.
      If you have a matrix data and information about the considered
     factors, then you can use 'neweS' to conver the data into exprSet.
     Please see 'neweS' in more detail. 
      eS is used only as an argument when calling 'msecalc' in the
     function.

_V_a_l_u_e:

bestsol : A vector containing best alpha and lambda value

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

     David Rocke and Geun-Cheol Lee

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

     <URL: http://www.idav.ucdavis.edu/~dmrocke/>

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

     'msecalc', 'tranest2'

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

     #library
     library(Biobase)
     library(LMGene)

     #data
     data(Smpd0)

     #
     mat1 <- as.matrix(Smpd0@exprs)
     lamstart <- log(median(abs(mat1))^2)
     alphastart <- quantile(abs(as.vector(mat1)), 0.1)
     startvar <- c(lamstart, alphastart)

     beams(Smpd0, startvar)

