surf.gls               package:spatial               R Documentation

_F_i_t_s _a _T_r_e_n_d _S_u_r_f_a_c_e _b_y _G_e_n_e_r_a_l_i_z_e_d _L_e_a_s_t-_s_q_u_a_r_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Fits a trend surface by generalized least-squares.

_U_s_a_g_e:

     surf.gls(np, covmod, x, y, z, nx=1000, ...)

_A_r_g_u_m_e_n_t_s:

      np: degree of polynomial surface 

  covmod: function to evaluate covariance or correlation function 

       x: x coordinates or a data frame with columns `x', `y', `z' 

       y: y coordinates 

       z: z coordinates. Will supersede `x$z' 

      nx: Number of bins for table of the covariance. Increasing adds
          accuracy, and increases size of the object. 

     ...: parameters for `covmod' 

_V_a_l_u_e:

     list with components 

    beta: the coefficients 

       x: 

       y: 

       z: and others for internal use only. 

_S_e_e _A_l_s_o:

     `trmat', `surf.ls', `prmat', `semat', `expcov', `gaucov',
     `sphercov'

_E_x_a_m_p_l_e_s:

     data(topo)
     topo.kr <- surf.gls(2, expcov, topo, d=0.7)
     trsurf <- trmat(topo.kr, 0, 6.5, 0, 6.5, 50)
     contour(trsurf)
     prsurf <- prmat(topo.kr, 0, 6.5, 0, 6.5, 50)
     contour(prsurf, levels=seq(700, 925, 25))
     sesurf <- semat(topo.kr, 0, 6.5, 0, 6.5, 30)
     contour(sesurf, levels=c(22,25))

