secal                package:splancs                R Documentation

_S_t_a_n_d_a_r_d _e_r_r_o_r_s _f_o_r _t_h_e _d_i_f_f_e_r_e_n_c_e _b_e_t_w_e_e_n _t_w_o _K-_f_u_n_c_t_i_o_n_s

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

     Calculate standard errors for the difference between two
     K-functions under random labelling of the corresponding two sets
     of points.

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

     secal(pts1,pts2,poly,s)

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

pts1,pts2: Two point data sets 

    poly: Polygon enclosing the points in `pts1' and `pts2' 

       s: A vector of distances at which to calculate the standard
          error. 

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

     A vector like `s' containing the value of the standard error at
     each of the distances in `s'

_M_E_T_H_O_D:

     To compare two point patterns, one can calculate the difference
     between their K-functions. The function `secal' gives the
     pointwise standard  errors for the estimated differences, under
     the random labelling hypothesis.

_R_e_f_e_r_e_n_c_e_s:

     Diggle P.J. and Chetwynd A.G. (1991) Second-order analysis of
     spatial  clustering Biometrics 47 1155-63;  Rowlingson, B. and
     Diggle, P. 1993 Splancs: spatial point pattern analysis code in
     S-Plus.  Computers and Geosciences, 19, 627-655; the original
     sources can be accessed at: <URL:
     http://www.maths.lancs.ac.uk/~rowlings/Splancs/>. See also Bivand,
     R. and Gebhardt, A. 2000 Implementing functions for spatial
     statistical analysis using the R language. Journal of Geographical
     Systems, 2, 307-317.

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

     `khat'

