copper               package:spatstat               R Documentation

_B_e_r_m_a_n-_H_u_n_t_i_n_g_t_o_n _p_o_i_n_t_s _a_n_d _l_i_n_e_s _d_a_t_a

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

     These data come from an intensive geological survey of a 70 x 158
     km region in central Queensland, Australia. They consist of 67
     points representing copper ore deposits, and 146 line segments
     representing geological `lineaments'. Lineaments are linear
     features, visible on a satellite image, that are believed to
     consist largely of geological faults (Berman, 1986, p. 55). It
     would be of great interest to predict the occurrence of copper
     deposits from the lineament pattern, since the latter can easily
     be observed on satellite images. 

     These data were introduced and analysed by Berman (1986). They
     have also been studied by Berman and Turner (1992), Baddeley and
     Turner (2000) and Foxall and Baddeley (2002).

     Many analyses have been performed on the southern half of the data
     only. This subset is also provided.

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

     data(copper)

_F_o_r_m_a_t:

     'copper' is a list with the following entries:

     _p_o_i_n_t_s an object of class '"ppp"' representing the full point
          pattern of copper deposits. See 'ppp.object' for details of
          the format.

     _l_i_n_e_s the coordinates of the lineaments in the full dataset, given
          as a data frame with 4 columns (x1, y1, x2, y2).

     _S_o_u_t_h_W_i_n_d_o_w the window delineating the southern half of the study
          region. An object of class '"owin"'.

     _S_o_u_t_h_P_o_i_n_t_s the point pattern of copper deposits in the southern
          half of the study region. An object of class '"ppp"'.

     _S_o_u_t_h_L_i_n_e_s the coordinates of the lineaments in the southern half
          of the study region. A data frame with 4 columns in format
          (x1, y1, x2, y2).

     _S_o_u_t_h_D_i_s_t_a_n_c_e A function with no arguments. The return value is a
          pixel image with greyscale value equal to the distance to the
          nearest lineament. Computed only inside the southern half of
          the dataset. An object of class '"im"'.

_S_o_u_r_c_e:

     Dr J. Huntington. Coordinates kindly provided by Dr. Mark Berman,
     CSIRO, Sydney, Australia.

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

     Baddeley, A. and Turner, R. (2000) Practical maximum
     pseudolikelihood for spatial point patterns. _Australian and New
     Zealand Journal of Statistics_ *42*, 283-322.

     Berman, M. (1986). Testing for spatial association between a point
     process and another stochastic process. _Applied Statistics_ *35*,
     54-62.

     Berman, M. and Turner, T.R. (1992) Approximating point process
     likelihoods with GLIM. _Applied Statistics_ *41*, 31-38.

     Foxall, R. and Baddeley, A. (2002) Nonparametric measures of
     association between a spatial point process and a random set, with
     geological applications. _Applied Statistics_ *51*, 165-182.

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

       data(copper)

       # Plot full dataset

       plot(copper$points)
       cl <- copper$lines
       segments(cl[,1], cl[,2], cl[,3], cl[,4])

       # Plot southern half of data
       plot(copper$SouthPoints)
       cl <- copper$SouthLines
       segments(cl[,1], cl[,2], cl[,3], cl[,4])

       ## Not run: 
         Z <- copper$SouthDistance()
         plot(Z)
         X <- copper$SouthPoints
         ppm(X, ~D, covariates=list(D=Z))
       
     ## End(Not run)

