stamFit-class              package:stam              R Documentation

_M_o_d_e_l _F_i_t _G_e_n_e_r_a_t_e_d _b_y _S_t_A_M

_D_e_s_c_r_i_p_t_i_o_n:

     Objects of this class hold a model fit as it is generated by
     structured analysis of  microarray data. The function 'stam.fit'
     returns such objects. They are handed on  to 'stam.predict' for
     predictions.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form  'new("stamFit", cv,
     exprs, alpha, delta, max.nodes, collapse.scnodes)', but it is 
     recommended to use the function 'stam.fit'.

_S_l_o_t_s:


     '_s_a_m_p_l_e._c_l_a_s_s_e_s': Object of class '"character"', class names for 
          each sample

     '_c_l_a_s_s._l_a_b_e_l_s': Object of class '"character"', one name for each 
          class

     '_p_r_i_o_r': Object of class '"numeric"', prior class probabilities 
          according to prevalence

     '_f_u_l_l._p_a_m_f_i_t': Object of class '"nsc"', PAM fit on all probesets

     '_a_l_p_h_a': Object of class '"numeric"', performance vs. redundancy 
          weight(s)

     '_b_e_t_a': Object of class '"numeric"', class weights, one per class

     '_d_e_l_t_a': Object of class '"numeric"', shrinkage level given by the
           user

     '_b_e_s_t._d_e_l_t_a': Object of class '"numeric"', shrinkage level used
          for  computing

     '_d_e_f_a_u_l_t._d_e_l_t_a': Object of class '"numeric"', default shrinkage 
          level suggested by 'stam.fit'

     '_s_c_o_r_e_s': Object of class '"matrix"', compound scores weighted 
          using the provided alpha(s)

     '_a_l_p_h_a._t_a_b': Object of class '"matrix"', results comparing alphas

     '_n_o_d_e._r_e_s_u_l_t_s': Object of class '"list"', performance, redundancy,
           sensitivity and specificity per node

     '_c_o_l_l_a_p_s_e._s_c_n_o_d_e_s': Object of class '"logical"', whether single 
          children nodes are removed after shrinkage

     See 'stamNet-class' for slots 'chip', 'root', 'chippkg',  'GOpkg',
     'nodes', 'leafs', 'inodes' and 'probes'.

_E_x_t_e_n_d_s:

     Class '"stamNet"', directly.

_M_e_t_h_o_d_s:


     _p_r_i_n_t 'signature(x = "stamFit")': print information on the model
          fit.

     _w_r_i_t_e_H_T_M_L 'signature(x = "stamFit")': generate HTML information on
          the  model fit, but using 'stam.writeHTML' is recommended.

_A_u_t_h_o_r(_s):

     Claudio Lottaz

_S_e_e _A_l_s_o:

     'stam.fit', 'stamNet-class'

