ebplots               package:EBarrays               R Documentation

_V_a_r_i_o_u_s _p_l_o_t_t_i_n_g _r_o_u_t_i_n_e_s _i_n _t_h_e _E_B_a_r_r_a_y_s _p_a_c_k_a_g_e

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

     Various plotting routines, used for diagnostic purposes

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

     checkCCV(data, useRank = FALSE, f = 1/2)
     plotMarginal(fit, data, kernel = "rect", n = 100,
                  bw = "nrd0", adjust = 1, ...)
     checkModel(data, model = c("gamma", "lognormal"),
                number = 9, nb = 10)
     checkConvergence(..., dropfirst = FALSE)

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

    data: data, as a ``matrix'' or ``exprSet''

 useRank: logical. If 'TRUE', ranks of means and c.v.-s are used in the
          scatterplot 

       f: 

     fit: object of class ``ebarraysEmFit'', typically produced by a
          call to 'emfit' 

kernel, n, bw, adjust: passed on to 'density'

   model: which theoretical model use for Q-Q plot. Partial string
          matching is allowed 

  number: number of subsets or bins (panels in the Trellis display) for
          which Q-Q plot is drawn 

      nb: number of observations per bin (panel) 

     ...: In the case of 'checkConvergence', matrices or vectors
          (treated as column vectors) with same number of rows. These
          are combined into a single matrix, then each column is scaled
          between 0 and 1 and plotted simultaneously.

          For 'plotMarginal', extra arguments are passed to the
          'xyplot' call used to produce the final result. 

dropfirst: logical. If 'TRUE', first row will be dropped 

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

     Needs to be written

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

     'plotMarginal' and 'checkModel' return an object of class
     ``trellis'', using function in the Lattice package. Note that in
     certain situations, these may need to be explicitly `print'-ed to
     have any effect.

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

     Christina Kendziorski, Michael Newton and Deepayan Sarkar

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

     'emfit', 'lowess'

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

     data(gould)
     checkCCV(gould)

