runifpoint             package:spatstat             R Documentation

_G_e_n_e_r_a_t_e _N _U_n_i_f_o_r_m _R_a_n_d_o_m _P_o_i_n_t_s

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

     Generate a random point pattern containing n independent uniform
     random points.

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

      runifpoint(n, win=owin(c(0,1),c(0,1)), giveup=1000)

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

       n: Number of points. 

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

  giveup: Number of attempts in the rejection method after which the
          algorithm should stop trying to generate new points. 

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

     This function generates 'n' independent random points, uniformly
     distributed in the window 'win'. (For nonuniform distributions,
     see 'rpoint'.)

     The algorithm depends on the type of window, as follows:

        *  If 'win' is a rectangle then  n independent random points,
           uniformly distributed in the rectangle, are generated by
           assigning uniform random values to their cartesian
           coordinates.

        *  If 'win' is a binary image mask, then a random sequence of 
           pixels is selected (using 'sample') with equal
           probabilities. Then for each pixel in the sequence we
           generate a uniformly distributed random point in that pixel.

        *  If 'win' is a polygonal window, the algorithm uses the
           rejection method. It finds a rectangle enclosing the window,
           generates points in this rectangle, and tests whether they
           fall in the desired window. It gives up when 'giveup * n'
           tests have been performed without yielding 'n' successes.

     The algorithm for binary image masks is faster than the rejection
     method but involves discretisation.

_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:

     'ppp.object', 'owin.object', 'rpoispp', 'rpoint'

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

      # 100 random points in the unit square
      pp <- runifpoint(100)
      # irregular window
      data(letterR)
      # polygonal
      pp <- runifpoint(100, letterR)
      # binary image mask
      pp <- runifpoint(100, as.mask(letterR))

