In this paper we introduce two general non-parametric first-order stationary time-series models for which marginal (invariant) and transition distributions are expressed as infinite-dimensional mixtures. That feature makes them the first Bayesian stationary fully non-parametric models developed...

It was in the 1990's when the concept of Operational Risk was defined, since then the institutions, especially those in the financial sector, are worried about this type of risk since their exposure could have fatal consequences. In case of the insurance sector its study originates due to the...

In the survey analysis, the missing data problem can be managed by using Multiple Imputation (MI) methods. In this paper we show the empirical application of MI methods to the financial variables included in Chile’s Social Protection Survey 2004. Based on

It was in the 1990’s when the concept of Operational Risk was defined, since then the institutions, especially those in the financial sector, are worried about this type of risk since their exposure could have fatal consequences. In case of the insurance sector its study originates due to the...

In this paper we introduce two general non-parametric first-order stationary time-series models for which marginal (invariant) and transition distributions are expressed as infinite-dimensional mixtures. That feature makes them the first Bayesian stationary fully non-parametric models developed...

The importance of the working document is that it allows the analysis of information and cases associated with (SARS-CoV-2) COVID-19, based on the daily information generated by the Government of Mexico through the Secretariat of Health, responsible for the Epidemiological Surveillance System...

The evolution of cities has led to changes in urban mobility patterns, including an increased number of trips, longer and more dispersed routes. Therefore, it is crucial to study urban mobility efficiently to promote sustainability and well-being. In this context, we reviewed the existing...

Research in the field of Artificial Intelligence has made considerable progress in recent years, demonstrating its effectiveness in predicting and classifying discrete decisions. However, these advances have been relatively underutilized in economic research due to the lack of links with...

This article aims to identify the most relevant variables that allow through a neural network model (RNA), with supervised learning, in a kind of error correction and feedforward perceptron multilayer architecture to achieve the best predictors of low risk, in the process of microcredit....

Innovation is increasingly recognized as a determinant of the level of economic activity; however, studies that analyze the determinants of innovation do not usually pay attention to the levels of development of the economies in which these processes occur. This paper aims to analyze whether the...