pimax                  package:mcsm                  R Documentation

_M_o_n_t_e _C_a_r_l_o _a_p_p_r_o_x_i_m_a_t_i_o_n _o_f _a _p_r_o_b_i_t _p_o_s_t_e_r_i_o_r _m_a_r_g_i_n_a_l

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

     This function represents the variability of a Monte Carlo
     approximation to the posterior distribution of the intercept of a
     probit model. The data used in this example is the Pima indian
     'Pima.tr' dataset. The function produces three plots, the top one
     being based on a single simulated sample for all values of the
     intercept along with the Monte Carlo variability estimated by 100
     repeated calls, the medium one being based on iid simulated
     samples for for all values of the intercept along with the
     corresponding Monte  Carlo variability and the bottom one being
     obtained by numerical integration.

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

     pimax(Nsim = 10^3)

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

    Nsim: Number of simulations in all Monte Carlo experiments

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

     Return three plots

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

     Christian P. Robert and George Casella

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

     From Chapter 5 of *EnteR Monte Carlo Statistical Methods*

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

     Pima.tr,pimamh

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

     ## Not run: pimax()

