batchSE                 package:coda                 R Documentation

_B_a_t_c_h _S_t_a_n_d_a_r_d _E_r_r_o_r

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

     Effective standard deviation of population to produce the correct
     standard errors.

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

     batchSE(x, batchSize=100)

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

       x: An 'mcmc' or 'mcmc.list' object.

batchSize: Number of observations to include in each batch.

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

     Because of the autocorrelation, the usual method of taking
     'var(x)/n' overstates the precision of the estimate.  This method
     works around the problem by looking at the means of batches of the
     parameter.  If the batch size is large enough, the batch means
     should be approximately uncorrelated and the normal formula for
     computing the standard error should work.

     The batch standard error procedure is usually thought to be not as
     accurate as the time series methods used in 'summary' and
     'effectiveSize'.  It is included here for completeness.

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

     A vector giving the standard error for each column of 'x'.

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

     Russell Almond

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

     Roberts, GO (1996) Markov chain concepts related to sampling
     algorithms, in Gilks, WR, Richardson, S and Spiegelhalter, DJ,
     _Markov Chain Monte Carlo in Practice_, Chapman and Hall, 45-58.

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

     'spectrum0.ar', 'effectiveSize', 'summary.mcmc'

