Continuous rank probability score

Calculates continuous rank probability score (CRPS) for probabilistic and ensemble forecasts
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更新 2014/9/11

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The CRPS measures the closeness of forecast distribution (fcst) and corresponding observation (obs). This score is widely used in forecast verification.

[mean_CRPS] = crps(fcst,obs);
[mean_CRPS] = crps(fcst,obs,plot_pos);
[mean_CRPS,crps_values,num] = crps(fcst,obs);

INPUT
obs: Vector of observations
fcst: Matrix of Ensemble forecast of size N x M. NB: N must equal length(obs), M equals the number of ensemble members
plot_pos: plotting positions that determine cumulative distribution function

OUTPUT
mean_CRPS: Mean of non missing CRPS values
crps_values: A vector (length n) of CRPS values
num: number of non missing CRPS values used to compute mean_CRPS

EXAMPLES:
fcst = rand(1000,1000);
obs = rand(1000,1);
[meanCRPS] = crps(fcst,obs);

引用格式

Durga Lal Shrestha (2026). Continuous rank probability score (https://ww2.mathworks.cn/matlabcentral/fileexchange/47807-continuous-rank-probability-score), MATLAB Central File Exchange. 检索时间: .

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