Regresión lineal con errores no normales: secante hiperbólica generalizada

This paper presents a study of the model of linear regression of the type y = Θx + e, where the error has generalized hyperbolic secant distribution (GHS) -- The method to estimate the parameters are obtained by setting maximum likelihood expressing the non-linear equations in linear form (modified likelihood) -- The resulting estimators are analytical expressions in terms of values of the sample and, therefore, are easily calculables -- Through the application of various types of data, the methodology described above is shown, and plausible models against the true underlying distributions of data are

• Autores: Burbano Moreno, Álvaro Alexander; Melo Martinez, Oscar Orlando
• Fecha de publicación: 2014
• Institución: Universidad EAFIT
• Repositorio: Repositorio EAFIT
• Idioma: spa
• OAI Identifier: oai:repository.eafit.edu.co:10784/5290
• Acceso en línea: http://hdl.handle.net/10784/5290
• Palabra clave: Ecuaciones no lineales; Funciones de verosimilitud; FUNCIONES EXPONENCIALES; MÍNIMOS CUADRADOS; ESTADÍSTICA MATEMÁTICA; ANÁLISIS DE REGRESIÓN; Functions, exponential; Least squares; Mathematical statistics; Regression analysis
• License: Copyright (c) 2015 Ingeniería y Ciencia – ing.cienc.