test1                  package:mcsm                  R Documentation

_P_o_o_r _c_h_i-_s_q_u_a_r_e _g_e_n_e_r_a_t_o_r

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

     This function is a direct implementation of the transform
     principle for the chi-square distribution, with poor performances
     even though the output is correct.

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

     test1(Nsim = 10^4, df = 6)

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

    Nsim: Number of simulations

      df: Degrees of freedom

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

     This function replicates 'rchisq(Nsim,df)' and thus should not be
     used.

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

     This function produces a numerical vector of size Nsim.

_w_a_r_n_i_n_g:

     For efficient chi-square simulation, make sure to use 'rchisq'

_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 2 of *EnteR Monte Carlo Statistical Methods*

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

     test2,rchisq

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

     mean(test1())
     # produces [1] 6.02526

