nbcosts                package:spdep                R Documentation

_C_o_m_p_u_t_e _c_o_s_t _o_f _e_d_g_e_s

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

     The cost of each edge is the distance between it nodes. This
     function compute this distance using a data.frame with
     observations vector in each node.

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

     nbcost(data, id, id.neigh,  method = c("euclidean", "maximum", 
         "manhattan", "canberra", "binary", "minkowski", "mahalanobis", 
         "other"), p = 2, cov, inverted = FALSE, otherfun)
     nbcosts(nb, data,  method = c("euclidean", "maximum", 
         "manhattan", "canberra", "binary", "minkowski", "mahalanobis", 
         "other"), p = 2, cov, inverted = FALSE, otherfun)

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

      nb: An object of 'nb' class. See 'poly2nb' for details.

    data: A matrix with observations in the nodes.

      id: Node index to compute the cost

id.neigh: Idex of neighbours nodes of node 'id'

  method: Character for declare the distance method.  For "euclidean",
          "maximum", "manhattan", "canberra",  "binary" and
          "minkowisk", see 'dist' for details,  because this function
          as used to compute the distance. If 'method="mahalanobis"',
          the mahalanobis distance is computed between neighbour areas.
          If 'method="other"', any function must be informed in
          'otherfun' argument.

       p: The power of the Minkowski distance.

     cov: The covariance matrix used to compute the mahalanobis 
          distance.

inverted: logical.  If 'TRUE', 'cov' is supposed to contain the inverse
          of the covariance matrix.

otherfun: A user defined function to compute the distance

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

     A object of 'nbdist' class. See 'nbdists' for details.

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

     Elias T. Krainski and Renato M. Assuncao

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

     See Also as 'nbdists', 'nb2listw'

