Expected distances and goodness-of-fit for the asymmetric Laplace distribution

2016 ◽  
Vol 117 ◽  
pp. 158-164 ◽  
Author(s):  
Maria L. Rizzo ◽  
John T. Haman
Keyword(s):  
Goodness Of Fit ◽  
Laplace Distribution ◽  
Asymmetric Laplace Distribution

Modélisation des erreurs pour le système de prévision PRÉVIS

2004 ◽  
Vol 31 (5) ◽  
pp. 892-897 ◽  
Author(s):  
Mario Lefebvre
Keyword(s):  
Statistical Models ◽  
Goodness Of Fit ◽  
Pareto Distribution ◽  
Laplace Distribution ◽  
Critical Threshold ◽  
Gaussian Distributions ◽  
Goodness Of Fit Tests ◽  
Generalized Pareto ◽  
Forecasting System

This paper examines models for the errors in forecasts of river and (or) watershed flows produced by the PREVIS forecasting system, which is used by Alcan, among other companies. We analyzed the following statistical models: generalized Pareto, Laplace, and Gaussian distributions, depending on the flow value forecasted by PREVIS. These models enable us to quantify the precision of the forecasts produced by PREVIS, as well as the risk of seeing the flow exceed a certain critical threshold, given the forecasted flow.Key words: modeling, Laplace distribution, Pareto distribution, goodness-of-fit tests, critical threshold.

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