rps               package:verification               R Documentation

_R_a_n_k_e_d _P_r_o_b_a_b_i_l_i_t_y _S_c_o_r_e

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

     Calculates the ranked probability score (rps) and ranked
     probability skill score (rpss) for probabilistic forecasts of
     ordered events.

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

      rps(obs, pred, baseline=NULL) 

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

     obs: A vector of observed outcomes.  These values correspond to
          columns of prediction probabilities.   

    pred: A matrix of probabilities for each outcome occurring.  Each
          column represents a category of prediction.

baseline: If NULL (default) the probability based on the sample data of
          each event to occur.    Alternatively,  a vector the same
          length of the as the number categories  can be entered. 

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

     rps: Ranked probability scores

    rpss: Ranked probability skill score.  Uses baseline or sample
          climatology as a references score.

rps.clim: Ranked probability score for baseline forecast.

_N_o_t_e:

     Perhaps the format of the data is best understood in the context
     of an example.  Consider a probability of precipitation forecast
     of "none", "light" or  "heavy".  This could be [0.5, 0.3, 0.2]. 
     If heavy rain occurred, the observed value would be 3, indicating
     event summarized in the third column occurred.

     *The RPS value is scaled to a [0,1 ] interval by dividing by
     (number of categories -1 .  There is a discrepancy in the way this
     is explained in Wilks (2005) and the WWRF web page. *

_A_u_t_h_o_r(_s):

     Matt Pocernich <pocernic@rap.ucar.edu>

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

     WWRP/WGNE Joint Working Group on Verification - Forecast
     Verification - Issues, Methods and FAQ <URL:
     http://www.bom.gov.au/bmrc/wefor/staff/eee/verif/verif_web_page.html#RPS>

     Wilks, D. S. (2005) _Statistical Methods in the Atmospheric
     Sciences _ Chapter 7, San Diego: Academic Press.

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

     'crps'

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

     ###  Example from Wilks, note without a baseline and only one
     ### forecast, the rpss and ss are not too meaningfull.


     rps( obs = c(1), pred = matrix(c(0.2, 0.5, 0.3), nrow = 1))

