autocorr                package:coda                R Documentation

_A_u_t_o_c_o_r_r_e_l_a_t_i_o_n _f_u_n_c_t_i_o_n _f_o_r _M_a_r_k_o_v _c_h_a_i_n_s

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

     `autocorr' calculates the autocorrelation function for the Markov
     chain `mcmc.obj' at the lags given by `lags'. The lag values are
     taken to be relative to the thinning interval if `relative=TRUE'.

     High autocorrelations within chains indicate slow mixing and,
     usually, slow convergence. It may be useful to thin out a chain
     with high autocorrelations before calculating summary statistics:
     a thinned chain may contain most of the information, but take up
     less space in memory. Re-running the MCMC sampler with a different
     parameterization may help to reduce autocorrelation.

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

     autocorr(mcmc.obj, lags = c(0, 1, 5, 10, 50), relative=TRUE 

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

     A vector or array containing the autocorrelations.

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

     Martyn Plummer

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

     `acf', `autocorr.plot'.

