monitor              package:R2WinBUGS              R Documentation

_S_p_e_c_i_a_l _s_u_m_m_a_r_y _s_t_a_t_i_s_t_i_c_s - _i_n_t_e_n_d_e_d _f_o_r _i_n_t_e_r_n_a_l _u_s_e _o_n_l_y

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

     Special summary statistics of the WinBUGS output - intended for
     internal use only

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

     monitor(a, n.chains, trans = NULL, keep.all = FALSE, Rupper.keep = FALSE)
     conv.par(x, n.chains, Rupper.keep = TRUE)

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

       x: 

       a: a 'n * m * k' array: 'm' sequences of length 'n', 'k'
          variables measured

n.chains: number of Markov chains

   trans: a vector of length 'k':  "" if no transformation, or "log" or
          "logit" (If 'trans' is 'NULL', it will be set to "log" for
          parameters that are all-positive and 0 otherwise.)

keep.all: if 'FALSE' (default), first half of 'a' will be discarded

Rupper.keep: if 'FALSE', don't return 'Rupper'

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

     See the well documented code for details.

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

     for 'monitor': 

  output: list of "mean","sd", quantiles
          ("2.5%","25%","50%","75%","97.5%"), "Rhat" if 'n.chains > 1',
           "Rupper" if '(Rupper.keep == TRUE) && (n.chains > 1)', and
          "n.eff" if 'n.chains > 1'

quantiles: emipirical quantiles of simulated sequences

confshrink: estimated potential scale reduction (that would be achieved
          by continuing simulations forever) has two components:  an
          estimate and an approx. 97.5% upper bound

   n.eff: effective sample size: 'm*n*min(sigma.hat^2/B,1)'. This is a
          crude measure of sample size because it relies on the between
          variance, 'B', which can only be estimated with m degrees of
          freedom.

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

     The main function to be called by the user is 'bugs'.

