stkhat                package:splancs                R Documentation

_S_p_a_c_e-_t_i_m_e _K-_f_u_n_c_t_i_o_n_s

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

     Compute the space-time K-functions

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

     stkhat(pts, times, poly, tlimits, s, tm)

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

     pts: A set of points as defined in Splancs 

   times: A vector of times, the same length as the number of points in
          'pts' 

    poly: A polygon enclosing the points 

 tlimits: A vector of length 2 specifying the upper and lower temporal
          domain. 

       s: A vector of spatial distances for the analysis. 

      tm: A vector of times for the analysis 

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

     A list with the following components is returned: 

    s, t: The spatial and temporal scales

      ks: The spatial K-function

      kt: The temporal K-function

     kst: The space-time K-function

     For details see Diggle, Chetwynd, Haggkvist, and Morris (1995)

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

     Diggle, P., Chetwynd, A., Haggkvist, R. and Morris, S. 1995
     Second-order analysis of space-time clustering. Statistical
     Methods in Medical Research, 4, 124-136;Bailey, T. C. and Gatrell,
     A. C. 1995, Interactive spatial data analysis. Longman, Harlow,
     pp. 122-125; 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:

     'stsecal', 'stvmat', 'stmctest', 'stdiagn'

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

     data(burkitt)
     bur1 <- stkhat(burpts, burkitt$t, burbdy, c(400, 5800),
       seq(1,40,2), seq(100, 1500, 100))
     oldpar <- par(mfrow=c(2,1))
     plot(bur1$s, bur1$ks, type="l", xlab="distance", ylab="Estimated K",
       main="spatial K function")
     plot(bur1$t, bur1$kt, type="l", xlab="time", ylab="Estimated K",
       main="temporal K function")
     par(oldpar)

