dmnorm              package:LearnBayes              R Documentation

_T_h_e _p_r_o_b_a_b_i_l_i_t_y _d_e_n_s_i_t_y _f_u_n_c_t_i_o_n _f_o_r _t_h_e _m_u_l_t_i_v_a_r_i_a_t_e _n_o_r_m_a_l (_G_a_u_s_s_i_a_n) _p_r_o_b_a_b_i_l_i_t_y _d_i_s_t_r_i_b_u_t_i_o_n

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

     Computes the density of a multivariate normal distribution

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

     dmnorm(x, mean = rep(0, d), varcov, log = FALSE)

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

       x: vector of length d or matrix with d columns, giving the
          coordinates of points where density is to evaluated

    mean: numeric vector giving the location parameter of the
          distribution

  varcov: a positive definite matrix representing the scale matrix of
          the distribution

     log: a logical value; if TRUE, the logarithm of the density is to
          be computed

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

     vector of density values

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

     Jim Albert

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

     mu <- c(1,12,2)
     Sigma <- matrix(c(1,2,0,2,5,0.5,0,0.5,3), 3, 3)
     x <- c(2,14,0)
     f <- dmnorm(x, mu, Sigma)

