stsecal               package:splancs               R Documentation

_S_t_a_n_d_a_r_d _e_r_r_o_r _f_o_r _s_p_a_c_e-_t_i_m_e _c_l_u_s_t_e_r_i_n_g

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

     Computes the standard error for space-time clustering.

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

     stsecal(pts, times, poly, tlim, 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 

    tlim: 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 matrix of dimension `[length(s),length(t)]' is returned. Element
      `[i,j]' is the standard error at `s[i],t[j]'. See Diggle Chetwynd
     Haggkvist and Morris (1995) for details.

_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:

     `stkhat', `stsecal', `stvmat', `stdiagn'

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

     example(stkhat)
     bur1se <- stsecal(burpts, burkitt$t, burbdy, c(400, 5800),
      seq(1,40,2), seq(100, 1500, 100))

