kernel3d               package:splancs               R Documentation

_S_p_a_c_e-_t_i_m_e _k_e_r_n_e_l

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

     Compute the space-time kernel

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

     kernel3d(pts, times, xgr, ygr, zgr, hxy, hz)

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

     pts: A matrix of event coodinates x,y. 

   times: A vector of event times, t. 

     xgr: The values of x at which to compute the kernel function. 

     ygr: The values of y at which to compute the kernel function. 

     zgr: The values of time at which to compute the kernel function. 

     hxy: The quartic kernel width in the x and y direction. 

      hz: The quartic kernel width in the temporal direction. 

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

     A list is returned. Most of the components are just copies of the 
     input parameters, except for the '$v' parameter. This is a three
     dimensional array containing the kernel-smoothed values. Its
     dimension is '[length(xgr),length(ygr),length(tgr)]'.

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

     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:

     'kerview'

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

     data(burkitt)
     b3d <- kernel3d(burpts, burkitt$t, seq(250,350,10), seq(250, 400, 10),
       seq(365,5800,365), 30, 200)
     brks <- quantile(b3d$v, seq(0,1,0.05))
     cols <- heat.colors(length(brks)-1)
     oldpar <- par(mfrow=c(3,5))
     for (i in 1:15) image(seq(250,350,10), seq(250, 400, 10), b3d$v[,,i],
       asp=1, xlab="", ylab="", main=1960+i, breaks=brks, col=cols)
     par(oldpar)

