histTailPP               package:BGmix               R Documentation

_H_i_s_t_o_g_r_a_m _p_l_o_t _f_o_r _t_a_i_l _p_o_s_t_e_r_i_o_r _p_r_o_b_a_b_i_l_i_t_y

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

     Plots a histogram of tail posterior probability with its density
     under the null hypothesis

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

     histTailPP(tpp.res, bw=0.05, xlim=c(0,1),nc=10)

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

 tpp.res: output of TailPP

      bw: bandwidth for kernel estimate of the null density

    xlim: limits on the x axis

      nc: number of bins of the histogram

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

     Natalia Bochkina

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

     Bochkina N., Richardson S. (2007)  Tail posterior probability for
     inference in pairwise and multiclass gene expression data.
     Biometrics.

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

     'TailPP', 'FDRplotTailPP','EstimatePi0'

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

     data(ybar, ss)
      nreps <- c(8,8)

     ## Note this is a very short MCMC run!
     ## For good analysis need proper burn-in period.
      outdir <- BGmix(ybar, ss, nreps, jstar=-1, nburn=0, niter=100, nthin=1)

      params <- ccParams(outdir)  
      res <-  ccTrace(outdir)
       
      tpp.res <- TailPP(res, nreps, params, plots  = FALSE)
      histTailPP(tpp.res, bw=0.04, xlim=c(0,1), nc=10)

