Mvnorm                package:mvtnorm                R Documentation

_T_h_e _M_u_l_t_i_v_a_r_i_a_t_e _N_o_r_m_a_l _D_i_s_t_r_i_b_u_t_i_o_n

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

     These functions provide information about the multivariate normal
     distribution with mean equal to 'mean' and covariance matrix
     'sigma'. 'dmvnorm' gives the density and 'rmvnorm' generates
     random deviates.

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

     dmvnorm(x, mean, sigma, log=FALSE)
     rmvnorm(n, mean, sigma)

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

       x: Vector or matrix of quantiles. If 'x' is a matrix, each row
          is taken to be a quantile.

       n: Number of observations.

    mean: Mean vector, default is 'rep(0, length = ncol(x))'.

   sigma: Covariance matrix, default is 'diag(ncol(x))'.

     log: Logical; if 'TRUE', densities d are given as log(d).

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

     Friedrich Leisch <Friedrich.Leisch@ci.tuwien.ac.at>

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

     'pmvnorm', 'rnorm', 'qmvnorm'

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

     dmvnorm(x=c(0,0))
     dmvnorm(x=c(0,0), mean=c(1,1))
     x <- rmvnorm(n=100, mean=c(1,1))
     plot(x)

