1997
DOI: 10.1016/0161-8938(95)00145-x
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Sensitivity analysis revisited: A quadrature-based approach

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Cited by 108 publications
(44 citation statements)
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“…The recently developed Gaussian Quadrature approach of DeVuyst and Preckel (1997) provides an attractive alternative. These authors show that an approximate distribution can be obtained based on known lower order moments of the parameters of a model, and that selectively solving the model based on the moments of this approximate distribution generates sensitivity results consistent with those of the Monte Carlo approach, with much more efficient use of computing time.…”
Section: Simulation and Ssamentioning
confidence: 99%
“…The recently developed Gaussian Quadrature approach of DeVuyst and Preckel (1997) provides an attractive alternative. These authors show that an approximate distribution can be obtained based on known lower order moments of the parameters of a model, and that selectively solving the model based on the moments of this approximate distribution generates sensitivity results consistent with those of the Monte Carlo approach, with much more efficient use of computing time.…”
Section: Simulation and Ssamentioning
confidence: 99%
“…However, it is impractical for large scale models. Therefore, we adopt the Gaussian Quadrature approach proposed by DeVuyst and Preckel (1997), who show that it is highly efficient and a very close approximation to full-blown Monte Carlo analysis of a similar, global CGE model. Here, we follow the implementation by Pearson and Arndt (2000).…”
Section: Ex Ante Analysis Of Eu and Us Biofuel Programsmentioning
confidence: 99%
“…Mediante el modelo se podía entonces inferir la distribución de probabilidad de las variables de salida vinculadas a la distribución de las perturbaciones de entrada. Esto se obtuvo realizando varias veces la simulación con distintos valores de entrada, mediante la técnica de cuadratura estadística de Stroud (Stroud, 1957;DeVuyst y Preckel, 1997). En consecuencia, no solo se produce información acerca de los valores centrales para todas las variables de salida, sino también sobre otros momentos estadísticos, como la desviación estándar.…”
Section: R E V I S T a C E P A L 1 1 1 • D I C I E M B R E 2 0 1 3 Ununclassified