algorithms              package:mvtnorm              R Documentation

_C_h_o_i_c_e _o_f _A_l_g_o_r_i_t_h_m _a_n_d _H_y_p_e_r _P_a_r_a_m_e_t_e_r_s

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

     Choose between two algorithms for evaluating normal distributions
     and define hyper parameters.

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

     GenzBretz(maxpts = 25000, abseps = 0.001, releps = 0)
     Miwa(steps = 128)

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

  maxpts: maximum number of function values as integer. 

  abseps: absolute error tolerance as double. 

  releps: relative error tolerance as double. 

   steps: number of grid points to be evaluated. 

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

     There are two algorithms available for evaluating normal
     probabilities: The default is the randomized Quasi-Monte-Carlo
     procedure by Genz (1992, 1993) and Genz and Bretz (2002)
     applicable to arbitrary covariance structures and dimensions up to
     1000.

     For smaller dimensions (up to 20) and non-singular covariance
     matrices, the algorithm by Miwa et al. (2003) can be used as well.

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

     An object of class 'GenzBretz' or 'Miwa'  defining hyper
     parameters.

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

     Genz, A. (1992). Numerical computation of multivariate normal
     probabilities. _Journal of Computational and Graphical
     Statistics_, *1*, 141-150.

     Genz, A. (1993). Comparison of methods for the computation of
     multivariate normal probabilities. _Computing Science and
     Statistics_, *25*, 400-405.

     Genz, A. and Bretz, F. (2002), Methods for the computation of
     multivariate t-probabilities. _Journal of Computational and
     Graphical Statistics_, *11*, 950-971.

     Miwa, A., Hayter J. and Kuriki, S. (2003). The evaluation of
     general non-centred orthant probabilities. _Journal of the Royal
     Statistical Society_, Ser. B, 65, 223-234.

