Cada vez son más numerosas las investigaciones que trabajan con un amplio número de variables donde existen relaciones complejas entre ellas. Las redes bayesianas son herramientas estadísticas surgidas en el campo de la Inteligencia Artificial que nos permiten afrontar situaciones de investigación de estas características. Una red bayesiana es un grafo dirigido acíclico que codifica relaciones probabilísticas de dependencia e independencia condicional y que actualiza el modelo con base en las evi-dencias muestrales mediante la regla de Bayes. Este artículo describirá los principios matemático-estadísticos esenciales de las redes bayesianas y las ventajas que tienen frente a otras herramientas multivariantes. Finalmente, revisaremos las apli...
We introduce the fundamental tenets of Bayesian inference, which derive from two basic laws of proba...
Bayesian methods have become increasingly popular in social sciences due to its flexibility in accom...
En este trabajo introduciremos los conceptos y contenidos probabilísticos sobre los que se fundament...
Bayesian Nets as Modelling Tools in Psychology. Abstract: There is more and more research projects w...
Cada vez son más numerosas las investigaciones que trabajan con un amplio número de variables donde ...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayes nets are a powerful tool for researchers in statistics and artificial intelligence. This chapt...
El mejoramiento de los métodos gráficos en la investigación en psicología puede promover su uso y un...
A Bayesian net is a kind of statistic modelling tool designed to represent a set of related uncertai...
Bayesian Networks are probabilistic graphical models that represent conditional independence relatio...
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various ...
Bayesian networks are tools that were developed by the Artificial Intelligence and Statistic communi...
Bayesian methods have become increasingly popular in social sciences due to its flexibility in accom...
Bayesian networks are directed acyclic graphs that code the relationships of conditional dependence...
Although the statistical tools most often used by researchers in the field of psychology over the la...
We introduce the fundamental tenets of Bayesian inference, which derive from two basic laws of proba...
Bayesian methods have become increasingly popular in social sciences due to its flexibility in accom...
En este trabajo introduciremos los conceptos y contenidos probabilísticos sobre los que se fundament...
Bayesian Nets as Modelling Tools in Psychology. Abstract: There is more and more research projects w...
Cada vez son más numerosas las investigaciones que trabajan con un amplio número de variables donde ...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayes nets are a powerful tool for researchers in statistics and artificial intelligence. This chapt...
El mejoramiento de los métodos gráficos en la investigación en psicología puede promover su uso y un...
A Bayesian net is a kind of statistic modelling tool designed to represent a set of related uncertai...
Bayesian Networks are probabilistic graphical models that represent conditional independence relatio...
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various ...
Bayesian networks are tools that were developed by the Artificial Intelligence and Statistic communi...
Bayesian methods have become increasingly popular in social sciences due to its flexibility in accom...
Bayesian networks are directed acyclic graphs that code the relationships of conditional dependence...
Although the statistical tools most often used by researchers in the field of psychology over the la...
We introduce the fundamental tenets of Bayesian inference, which derive from two basic laws of proba...
Bayesian methods have become increasingly popular in social sciences due to its flexibility in accom...
En este trabajo introduciremos los conceptos y contenidos probabilísticos sobre los que se fundament...