decluster                package:evir                R Documentation

_D_e_c_l_u_s_t_e_r _P_o_i_n_t _P_r_o_c_e_s_s

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

     Declusters clustered point process data so that Poisson assumption
     is more tenable over a high threshold.

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

     decluster(series, run = NA, picture = TRUE)

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

  series: a numeric vector of threshold exceedances with a 'times'
          attribute which should be a numeric vector containing either
          the indices or the times/dates of each exceedance (if
          times/dates, the attribute should be an object of class
          '"POSIXct"' or an object that can be converted to that class;
          see 'as.POSIXct')

     run: parameter to be used in the runs method; any two consecutive
          threshold exceedances separated by more than this number of
          observations/days are considered to belong to different
          clusters

 picture: whether or not a picture of declustering should be drawn

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

     The declustered object.

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

     Embrechts, P., Klueppelberg, C., Mikosch, T. (1997). _Modelling
     Extremal Events_. Springer. Chapter 8, 413-429.

_S_e_e _A_l_s_o:

     'pot', 'exindex', 'as.POSIXct'

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

     # decluster the 200 exceedances of a particular threshold in 
     # the negative BMW data
     data(bmw)
     out <- pot(-bmw, ne = 200) 
     decluster(out$data, 30) 

