simnewsamples              package:gaga              R Documentation

_P_o_s_t_e_r_i_o_r _p_r_e_d_i_c_t_i_v_e _s_i_m_u_l_a_t_i_o_n

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

     Simulates parameters and data from the posterior and posterior
     predictive distributions, respectively, of a GaGa or MiGaGa model.

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

     simnewsamples(gg.fit, groupsnew, sel, x, groups)

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

  gg.fit: GaGa or MiGaGa fit (object of type 'gagafit', as returned by
          'fit.gg').

groupsnew: Vector indicating the group that each new sample should
          belong to. 'length(groupsnew)' is the number of new samples
          that will be generated.

     sel: Numeric vector with the indexes of the genes we want to draw
          new samples for (defaults to all genes). If a logical vector
          is indicated, it is converted to '(1:nrow(x))[sel]'.

       x: 'ExpressionSet', data frame or matrix containing the gene
          expression measurements used to fit the model.

  groups: If 'x' is of type 'ExpressionSet', 'groups' should be the
          name of the column in 'pData(x)' with the groups that one
          wishes to compare. If 'x' is a matrix or a data frame,
          'groups' should be a vector indicating to which group each
          column in x corresponds to.

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

     The shape parameters are actually drawn from a gamma approximation
     to their posterior distribution. The function 'rcgamma' implements
     this approximation.

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

     List with the following components: 

    xnew: Matrix of 'length(nsel)' rows and 'length(groupsnew)' columns
          with observations drawn from the posterior predictive.

    dnew: Matrix with same dimensions as 'xnew' with with expression
          patterns drawn from the posterior.

    anew: Matrix with same dimensions as 'xnew' with with shape
          parameters drawn from the posterior.

    lnew: Matrix with same dimensions as 'xnew' with with mean
          expression drawn from the posterior.

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

     David Rossell

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

     Rossell D. GaGa: a simple and  flexible hierarchical model for
     microarray data analysis. <URL:
     http://rosselldavid.googlepages.com>.

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

     'checkfit' for posterior predictive plot, 'sim.gg' for prior
     predictive simulation.

