mycontour             package:LearnBayes             R Documentation

_C_o_n_t_o_u_r _p_l_o_t _o_f _a _b_i_v_a_r_i_a_t_e _d_e_n_s_i_t_y _f_u_n_c_t_i_o_n

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

     For a general two parameter density, draws a contour graph where
     the contour lines are drawn at 10 percent, 1 percent, and .1
     percent of  the height at the mode.

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

     mycontour(logf,limits,data)

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

    logf: function that defines the logarithm of the  density

  limits: limits (xlo, xhi, ylo, yhi) where the graph is to be drawn

    data: vector or list of parameters associated with the function
          logpost

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

     A contour graph of the density is drawn

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

     Jim Albert

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

     lbinorm=function(xy,par)
     {
             m=par$m
             v=par$v
             x=xy[,1]
             y=xy[,2]
             zx=(x-m[1])/sqrt(v[1,1])
             zy=(y-m[2])/sqrt(v[2,2])
             r=v[1,2]/sqrt(v[1,1]*v[2,2])
             return(-.5/(1-r^2)*(zx^2-2*r*zx*zy+zy^2))
     }
     m=array(c(0,0),c(2,1))
     v=array(c(1,.6,.6,1),c(2,2))
     normpar=list(m=m,v=v)
     mycontour(lbinorm,c(-4,4,-4,4),normpar)

