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Prueba de homogeneidad de varianzas para muestras normales censuradas. Colegio de Postgraduados
Huerta Contreras, Violeta de la.
El ANOVA es ampliamente usado en diversos campos de la investigaci on, es por ello que veri car el cumplimiento de los supuestos es muy importante; especialmente el de homogeneidad de varianzas. Actualmente existen una buena cantidad de pruebas para este ultimo, sin embargo se tiene una limitante en el ambito pr actico cuando la muestra es censurada. El objetivo de este trabajo fue investigar el comportamiento de la prueba de Bartlett bajo censura por la derecha del tipo II. Se utiliza el m etodo de m axima verosimilitud para estimar las varianzas, se investiga el comportamiento asint otico (m etodo Delta) del estad stico de prueba bajo censura y por medio del m etodo Monte Carlo a 10,000 repeticiones (donde tanto el tama~no y censura de n1 sea = o 6=...
Palavras-chave: ANOVA; Censura por la derecha; Método delta; Prueba de Bartlett; Prueba de Levene; Reproducción animal; Bartlett's test; Delta method; Levene's test; Right censure type II; Animal reproduction; Maestría; Estadística.
Ano: 2012 URL: http://hdl.handle.net/10521/677
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Les méthodes delta en halieutique. Evaluation des sensibilites, approximation des biais et variances à l'aide de developpements limites ArchiMer
Laurec, Alain.
This report presents an introduction to so called "delta methods", associated to the use of Taylor's expansions, as a tool for sensitivity analyses. It starts with a mathematical and statistical summary about Taylor's expansion and moments of random variâtes. Special attention is paid to multivariate problems. The application of order 1 and 2 expansions to estimate variances and biases is exposed in great details. This report dedicated to fisheries scientists, is finally illustraded by an example associated to yield per recruit calculations, based upon JONE'S length cohort analysis.
Tipo: Text Palavras-chave: Analyse des cohortes; Rendement par recrue; Méthode delta; Sensibilité; Length cohort analysis; Yield per recruit; Delta method; Sensitivity.
Ano: 1987 URL: https://archimer.ifremer.fr/doc/1987/rapport-1565.pdf
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The Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification AgEcon
Bernard, Jean-Thomas; Gavin, Michael; Khalaf, Lynda; Voia, Marcel.
We consider an empirical estimation of the Environmental Kuznets Curve (EKC) for carbon dioxide and sulphur, with a focus on confidence set estimation of the tipping point. Various econometric – parametric and nonparametric – methods are considered, reflecting the implications of persistence, endogeneity, the necessity of breaking down our panel regionally, and the small number of countries within each panel. In particular, we propose an inference method that corrects for potential weak-identification of the tipping point. Weak identification may occur if the true EKC is linear while a quadratic income term is nevertheless imposed into the estimated equation. Relevant literature to date confirms that non-linearity of the EKC is indeed not granted, which...
Tipo: Working Paper Palavras-chave: Environmental Kuznets Curve; Fieller method; Delta method; CO2 and SO2 emissions; Confidence set; Tipping point; Climate policy; Environmental Economics and Policy; C52; Q51; Q52; Q56.
Ano: 2011 URL: http://purl.umn.edu/119109
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Confidence intervals for predicted outcomes in regression models for categorical outcomes AgEcon
Xu, Jun; Long, J. Scott.
We discuss methods for computing confidence intervals for predictions and discrete changes in predictions for regression models for categorical outcomes. The methods include endpoint transformation, the delta method, and bootstrapping. We also describe an update to prvalue and prgen from the SPost package, which adds the ability to compute confidence intervals. The article provides several examples that illustrate the application of these methods.
Tipo: Journal Article Palavras-chave: Prvalue; Prgen; Confidence interval; Predicted probability; Discrete choice models; Endpoint transformation; Delta method; Bootstrap; Research Methods/ Statistical Methods.
Ano: 2005 URL: http://purl.umn.edu/117544
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