tranest2               package:LMGene               R Documentation

_G_l_o_g _t_r_a_n_s_f_o_r_m_a_t_i_o_n _p_a_r_a_m_e_t_e_r _e_s_t_i_m_a_t_i_o_n _f_u_n_c_t_i_o_n _2

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

     A sub-function of 'tranest' which search the best parameters for
     glog transformation.

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

     tranest2(eS, starting = FALSE, lambda = 1000, alpha = 0, gradtol = 0.001, lowessnorm, method=1, model=NULL)

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

      eS: Array data. must be exprSet type. 

starting: TRUE, if the given initial parameter values are used 

  lambda: Initial parameter value for lambda 

   alpha: Initial parameter value for alpha 

 gradtol: a positive scalar giving the tolerance at which the scaled
          gradient is considered close enough to zero to terminate the
          algorithm 

lowessnorm: TRUE, if lowess method is going to be used 

  method: Set optimization method; default is modified Gauss-Newton
          (nlm). See 'tranest'.

   model: Model in terms of vlist which is compared to transformed
          expression data. See 'tranest'.

_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. 'model' is an optional
     character string, constructed like the right-hand side of a
     formula for lm. It specifies which of the variables in the exprSet
     will be used in the model and whether interaction terms will be
     included. If model=NULL, it uses all variables from the exprSet
     without interactions. Be careful of using interaction terms with
     factors: this often leads to overfitting, which will yield an
     error.

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

tranpar : A numeric vector containing the best parameter for 'lambda'
          and 'alpha'

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

     David Rocke and Geun-Cheol Lee

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

     B. Durbin and D.M. Rocke, (2003) Estimation of Transformation
     Parameters for Microarray Data,  Bioinformatics, 19, 1360-1367.

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

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

     'jggrad2', 'tranest2'

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

     #library
     library(Biobase)
     library(LMGene)

     #data
     data(sample.eS)

     tranpar <- tranest2(sample.eS, lambda= 500, alpha=50)
     tranpar

