Modelo Regresión de Conteo
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Fecha
2017-10
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Jaén: Universidad de Jaén
Resumen
[ES]En este Trabajo Fin de Grado (TFG) que exponemos es una iniciación en los modelos
de conteo. El tema central es el desarrollo y usos de los modelos de conteo, en concreto
Distribución Poisson y Distribución Binomial Negativa. Estudiamos el método de llevar
a cabo el desarrollo econométrico de una observación. El planteamiento principal del
trabajo es la comprensión y desenvolvimiento de estos dos modelos, estudiando cómo
llegar hasta ellos con los conocimientos del modelo básico estudiado anteriormente,
Modelo Lineal. Experimentando su uso con el programa informático Gretl. Poniendo en
práctica mediante un ejemplo la compresión de estos, estableciendo diferentes modelos,
comprobando la dependencia de las variables mediante hipótesis, teniendo en cuenta las
diferentes las posibilidades que nos dan las variables de la observación.
[EN]This Final Project Grade (TFG) which we expose it is an initiation into Models of Count. The central theme is the development and uses of count models, in particular Poisson Distribution and the Negative Binomial Distribution. We studied the method of carrying out econometric development of an observation. The main approach to the work is the understanding and development of these two models, studying how to get them with the knowledge of the basic model studied previously, Linear Model. Experiencing the process in the Gretl software. Putting into practice through an example of these compressions, setting different models, checking the dependence of the variables using hypothesis, taking into account the different possibilities that give us the variables of the observation.
[EN]This Final Project Grade (TFG) which we expose it is an initiation into Models of Count. The central theme is the development and uses of count models, in particular Poisson Distribution and the Negative Binomial Distribution. We studied the method of carrying out econometric development of an observation. The main approach to the work is the understanding and development of these two models, studying how to get them with the knowledge of the basic model studied previously, Linear Model. Experiencing the process in the Gretl software. Putting into practice through an example of these compressions, setting different models, checking the dependence of the variables using hypothesis, taking into account the different possibilities that give us the variables of the observation.