We propose an objective Bayesian method for the comparison of all Gaussian directed acyclic graphical models defined on a given set of variables. The method, which is based on the notion of fractional Bayes factor, requires a single default (typically improper) prior on the space of...

Switching model, we estimate the demand for mortgage using aggregate monthly data from January 2003 to September 2012. The results show that this variable has been subject to cycles of contraction and expansion since 2003. The boom starts at the end of 2005 is marked by the alternation of two...

The analysis of technical efficiency (TE) on the small-scale fishery is relevant for several reasons. While this type of fishery is highly common in developing countries like Mexico, there are a very limited number of analyses assessing their efficiency. Indeed, there is no precise information...

Abstract Multivariate regression models and ANOVA are probably the most frequently applied methods of all statistical analyses. We study the case where the predictors are qualitative variables and the response variable is quantitative. In this case, we propose an alternative to the classic...

Abstract We develop a mathematical and interpretative foundation for the enterprise of decision-theoretic (DT) statistical causality, which is a straightforward way of representing and addressing causal questions. DT reframes causal inference as “assisted decision-making” and aims to...

Locating fed cattle price discovery center is revisited using the framework that combines recent progress in causal research with time series analysis. The Bernanke factorization in innovation accounting is obtained by a graphical method called directed acyclic graph which uses data to identify...

A special class of preferences, given by a directed acyclic graph, is considered. They are represented by incomplete pairwise comparison matrices as only partial information is available: for some pairs no comparison is given in the graph. A weighting method satisfies the property linear order...

The Instrumental Variable (IV) formula has become widely used to address the issue of identification of a causal effect in linear systems with an unobserved variable that acts as direct confounder. We here propose two alternative formulations to achieve identification when the assumptions...

Given a target variable and observational data, we propose a sequential learning approach for discovering direct cause and effect variables of the target under the causal network framework. In the approach, we start from the target, sequentially find Markov blankets of variables and learn local...

In this work, we consider the topological analysis of symbolic formal systems in the framework of network theory. In particular, we analyse the network extracted by Principia Mathematica of B. Russell and A.N. Whitehead, where the vertices are the statements and two statements are connected with...