kernrat               package:splancs               R Documentation

_R_a_t_i_o _o_f _t_w_o _k_e_r_n_e_l _s_m_o_o_t_h_i_n_g_s

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

     Return the ratio of two kernel smoothings

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

     kernrat(pts1,pts2,poly,h1,h2,nx=20,ny=20,kernel='quartic')

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

pts1,pts2: Point data sets 

    poly: A polygon data set 

   h1,h2: The kernel width parameters, 'h1' for 'pts1', and 'h2' for
          'pts2' 

      nx: Number of points along the x-axis of the returned grid. 

      ny: Number of points along the y-axis of the returned grid. 

  kernel: Type of kernel function to use. Currently only the quartic
          kernel is implemented. 

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

     A list with the following components: 

       x: List of x-coordinates at which the kernel function has been
          evaluated.

       y: List of y-coordinates at which the kernel function has been
          evaluated.

       z: A matrix of dimension 'nx' by 'ny' containing the ratio of
          the kernel functions.

       h: A vector of length 2 containing 'h1' and 'h2'

  kernel: a character string containing the kernel name.

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

     Berman M. and Diggle P.J. (1989) Estimating Weighted Integrals of
     the Second-Order Intensity of Spatial Point Patterns. _J. R.
     Statist Soc_ B51 81-92; 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:

     'kernel2d', 'mse2d'

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

     data(okwhite)
     data(okblack)
     okpoly <- list(x=c(okwhite$x, okblack$x), y=c(okwhite$y, okblack$y))
     kr <- kernrat(as.points(okwhite), as.points(okblack), bboxx(bbox(as.points(okpoly))),
      h1=50, h2=50)
     image(kr, asp=1)
     brks <- quantile(c(kr$z), seq(0,1,1/10), na.rm=TRUE)
     lbrks <- formatC(brks, 3, 6, "g", " ") 
     cols <- heat.colors(length(brks)-1)
     def.par <- par(no.readonly = TRUE)
     layout(matrix(c(1,0,1,2), 2, 2, byrow = TRUE), c(2.5,1.5), c(1,3), TRUE)
     image(kr, breaks=brks, col=cols, asp=1)
     plot.new()
     legend(c(0,1), c(0,1), legend=paste(lbrks[-length(lbrks)], lbrks[-1], sep=":"), fill=cols, bty="n")
     par(def.par)

