rMatClust              package:spatstat              R Documentation

_S_i_m_u_l_a_t_e _M_a_t_e_r_n _C_l_u_s_t_e_r _P_r_o_c_e_s_s

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

     Generate a random point pattern using the Mat\'ern Cluster
     Process.

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

      rMatClust(lambda, r, mu, win = owin(c(0,1),c(0,1)))

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

  lambda: Intensity of the Poisson process of cluster centres. A single
          positive number. 

       r: Radius parameter of the clusters. 

      mu: Mean number of points per cluster. 

     win: Window in which to simulate the pattern. An object of class
          `"owin"' or something acceptable to `as.owin'. 

_D_e_t_a_i_l_s:

     This algorithm generates a realisation of Mat\'ern's cluster
     process inside the window `win'. The process is constructed by
     first generating a uniform Poisson point process of ``parent''
     points  with intensity `lambda'. Then each parent point is
     replaced by a random cluster of points, the number of points in
     each cluster being random with a Poisson (`mu') distribution, and
     the points being placed independently and uniformly inside a disc
     of radius `r' centred on the parent point.

     In this implementation, parent points are not restricted to lie in
     the window; the parent process is effectively the uniform Poisson
     process on the infinite plane.

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

     The simulated point pattern (an object of class `"ppp"').

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

     Adrian Baddeley adrian@maths.uwa.edu.au <URL:
     http://www.maths.uwa.edu.au/~adrian/> and Rolf Turner
     rolf@math.unb.ca <URL: http://www.math.unb.ca/~rolf>

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

     `rpoispp', `rNeymanScott'

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

      pp <- rMatClust(10, 0.05, 4)

