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      Evaluación de factores de corrección para estimar incertidumbres de distribuciones triangulares con intervalos de cobertura del 95% Translated title: Evaluation of correction factors to estimate the uncertainties of triangular distributions with 95% coverage intervals

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          Abstract

          Resumen Recientemente, la estimación de incertidumbre se convirtió en un requisito metrológico de gran interés para el reporte de inventarios de gases de efecto invernadero en Costa Rica. En este contexto, una guía metodológica del Programa País de Carbono Neutralidad ha surgido como base para el desarrollo local de esta temática. Sin embargo, algunos aspectos de su contenido requieren esfuerzos adicionales que permitan brindar una explicación técnica clara que justifique su implementación. El presente estudio evalúa la validez del uso de factores de corrección (FC), propuestos por esta guía, que amplían la incertidumbre estándar estimada mediante el ajuste una distribución triangular, en presencia de un intervalo de cobertura del 95 %. Para ello, se simularon 3124 escenarios de distribuciones triangulares utilizando el software estadístico R y se les estimó una incertidumbre estándar considerando que los límites simulados delimitan un intervalo de cobertura al 100 % (u100) y un intervalo de cobertura al 95 % (u95), evaluando además dos posibles interpretaciones sobre la ubicación de este último. Los FC se estimaron para cuatro grupos como las razones promedio entre u95y u100. Se obtuvieron FC entre 1,20 y 1,29, con un valor global de 1,25 y sin presentarse diferencias significativas entre ellos. Estos valores son altamente consistentes con los recomendados en la guía metodológica nacional, comprobando así su validez y aplicabilidad. Finalmente, se sugiere el uso de un único FC igual a 1,25 como aproximación simple y práctica para todos los escenarios evaluados, facilitando su implementación homologada por los usuarios.

          Translated abstract

          Abstract Recently, uncertainty estimation has become a metrological requirement of great interest for the reporting of greenhouse gas inventories in Costa Rica. In this context, a methodological guide published by the National Carbon Neutrality Program has emerged as the basis for the local development of this issue. However, additional efforts are still pending to provide a clear technical explanation that justifies the implementation of some aspects of its content. The present study assesses the validity of the use of correction factors (FC), proposed by this guide, that enlarges the standard uncertainty estimated from a triangular distribution, in the presence of a 95 % coverage interval. To achieve this, 3124 triangular distribution scenarios were simulated using R statistical software. Two standard uncertainties were estimated for each scenario: one considering that the simulated limits delimit a 100 % coverage interval (u100) and another considering a 95 % coverage interval (u95), with two possible interpretations about the location of the interval for the latter. FC were estimated for four groups as the mean ratio between u95 and u100. Results between 1.20 and 1.29 were obtained for FC, with a global value of 1.25 and no significant differences between them. These values are highly consistent with those recommended in the national methodological guide, thus verifying their validity and applicability. Finally, a unique FC equal to 1.25 is suggested as a simple practical approximation for all the evaluated scenarios, easing its implementation by users.Keywords:

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          Most cited references19

          • Record: found
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          Numerical Methods for Unconstrained Optimization and Nonlinear Equations

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            • Abstract: not found
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            Greenhouse gases — Part 1: Specification with guidance at the organization level for quantification and reporting of greenhouse gas emissions and removals.

              • Record: found
              • Abstract: not found
              • Article: not found

              ''VIM – Vocabulario Internacional de Metrología. Conceptos fundamentales y generales, y términos asociados (VIM 2008 con pequeñas correcciones)''.

              (2008)

                Author and article information

                Journal
                ingenieria
                Ingeniería
                Ingeniería
                Universidad de Costa Rica (San José, San José, Costa Rica, Costa Rica )
                1409-2441
                2215-2652
                December 2022
                : 32
                : 2
                : 15-31
                Affiliations
                [1] orgnameLCM Costa Rica gmolina@ 123456lcm.go.cr
                Article
                S2215-26522022000200015 S2215-2652(22)03200200015
                10.15517/ri.v32i2.49699
                d724510b-e6a5-4a58-8de5-53ba5acd632f

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

                History
                : 11 January 2022
                : 28 April 2022
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 19, Pages: 17
                Product

                SciELO Costa Rica

                Categories
                Artículo

                simulación,uncertainty,incertidumbre,gases de efecto invernadero,distribución triangular,Distribución de probabilidad,Programa País de Carbono Neutralidad,Greenhouse gases,National Program for Carbon Neutrality,probability distribution,simulation,triangular distribution

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