52 research outputs found
A non-parametric independence test using permutation entropy
In the present paper we construct a new, simple and powerful test for independence by
using symbolic dynamics and permutation entropy as a measure of serial dependence.
We also give the asymptotic distribution of an affine transformation of the permutation
entropy under the null hypothesis of independence. An application to several daily
financial time series illustrates our approach
Net energy analysis in a Ramsey-Hotelling growth model
This article presents a dynamic growth model with energy as an input in the production function. The available stock of energy resources is ordered by a quality parameter based on energy accounting: the “Energy Return on Energy Invested” (EROI). To our knowledge this is the first paper where EROI fits in a neoclassical growth model (with individual utility maximization and market equilibrium), setting the economic use of “net energy analysis” on firmer theoretical ground. All necessary concepts to link neoclassical economics and EROI are discussed before their use in the model, and a comparative static analysis of the steady states of a simplified version of the model is presentedEste artículo presenta un modelo de crecimiento dinámico con la energía como un input en la función de producción. El stock de recursos energéticos disponibles se ordena por un parámetro de calidad basado en la contabilidad energética: la tasa de retorno energético (TRE). Por lo que sabemos esta es la primera vez que la TRE encaja en modelo de crecimiento neoclásico (con maximización individual de la utilidad y equilibrio de mercado) estableciendo así el uso del “análisis de rendimiento energético" sobre una base teórica más firme. Todos los conceptos necesarios para enlazar la economía neoclásica con la TRE se discuten antes de ser usados en el modelo, y se presenta un análisis comparativo del estado estacionario de una versión simplificada del model
Spanish Market Integration at the end of the 19th Century. Wheat Prices between 1891 and 1905
The degree of development of Spanish agriculture at the end of the XIX century and the beginning of XX is a controversial issue. In this respect the study of the integration of the domestic market could provide new evidence since the degree of the market integration can be considered an indicator of economic development. By using regional wheat prices this paper analyzes the Spanish market integration between 1891 and 1905. With this aim in mind we employ the usual cointegration approach as well as an alternative method based on spectral analysis that allows taking into consideration the existence of no synchronized cycles.El grado de desarrollo de la agricultura española a finales del siglo XIX y principios de XX es una cuestión controvertida y el análisis de la integración del mercado interior puede aportar evidencias que contribuyan a matizar esta tesis. En general se considera que el grado de integración de mercado es un indicador del desarrollo económico. Este trabajo analiza empíricamente la cuestión de la integración del mercado interior entre 1891 y 1905 a partir de los precios del trigo de las diferentes regiones. A tal fin se presenta además del modelo de cointegración predominante en la actualidad un mètodo alternativo, la descomposición espectral, que permite tomar en consideración la existencia de ciclos no sincronizados
Two Tests for Dependence (of Unknown Form) between Time Series
This paper proposes two new nonparametric tests for independence between time series. Both tests are based on symbolic analysis, specifically on symbolic correlation integral, in order to be robust to potential unknown nonlinearities. The first test is developed for a scenario in which each considered time series is independent and therefore the interest is to ascertain if two internally independent time series share a relationship of an unknown form. This is especially relevant as the test is nuisance parameter free, as proved in the paper. The second proposed statistic tests for independence among variables, allowing these time series to exhibit within-dependence. Monte Carlo experiments are conducted to show the empirical properties of the tests.This research is the result of the activity performed under the program Groups of Excellence of the Region of Murcia, the Fundación Seneca, Science and Technology Agency of the region of Murcia project under grant 19884/GERM/15. All remaining errors are our responsibility
Symbolic Recurrence Analysis of RR Interval to Detect Atrial Fibrillation
Atrial fibrillation (AF) is a sustained cardiac arrhythmia associated with stroke, heart failure, and related health conditions. Though easily diagnosed upon presentation in a clinical setting, the transient and/or intermittent emergence of AF episodes present diagnostic and clinical monitoring challenges that would ideally be met with automated ambulatory monitoring and detection. Current approaches to address these needs, commonly available both in smartphone applications and dedicated technologies, combine electrocardiogram (ECG) sensors with predictive algorithms to detect AF. These methods typically require extensive preprocessing, preliminary signal analysis, and the integration of a wide and complex array of features for the detection of AF events, and are consequently vulnerable to over-fitting. In this paper, we introduce the application of symbolic recurrence quantification analysis (SRQA) for the study of ECG signals and detection of AF events, which requires minimal pre-processing and allows the construction of highly accurate predictive algorithms from relatively few features. In addition, this approach is robust against commonly-encountered signal processing challenges that are expected in ambulatory monitoring contexts, including noisy and non-stationary data. We demonstrate the application of this method to yield a highly accurate predictive algorithm, which at optimal threshold values is 97.9% sensitive, 97.6% specific, and 97.7% accurate in classifying AF signals. To confirm the robust generalizability of this approach, we further evaluated its performance in the implementation of a 10-fold cross-validation paradigm, yielding 97.4% accuracy. In sum, these findings emphasize the robust utility of SRQA for the analysis of ECG signals and detection of AF. To the best of our knowledge, the proposed model is the first to incorporate symbolic analysis for AF beat detection.This research was funded by projects AIM, ref. TEC2016-76465-C2-1-R (AEI/FEDER, UE), e-DIVITA,
ref.20509/PDC/18 (Proof of Concept, 2018) and it is the result of the activity performed under the program Groups
of Excellence of the Region of Murcia (Spain), the Fundación Séneca, Science and Technology Agency of the
region of Murcia project under grant 19884/GERM/15 and ATENTO, ref. 20889/PI/18. All remaining errors are
our responsibility
Hernias diafragmáticas traumáticas
The diafragm is a thin and flat musculo-fascial structure that separates the chest from the abdominal cavity.Traumatic diaphragmatic hernia is an infrequent and life-threatening injury that may happen in patients with severe blunt or penetrating thoracoabdominal trauma. Diaphragmatic rupture is an important indicator of the severity of the trauma.These ruptures may be recognized at the time of the initial trauma, but are diagnosed months or even years later during the follow-up for related symptoms. If it is not detected early, the mortality rate could increase due to severe complications.The diagnosis of traumatic diaphragmatic hernia is difficult and often missed, because it could be accompanied by injuries to other organs. Supine chest radiography, despite its known limitations, is the initial most commonly performed imaging test to evaluate a traumatic injury in the thorax. However, computed tomography (CT) is the imaging tool of choice, as it is the key element for the detection of diaphragmatic injury after trauma.In hemodynamically stable patients, either videolaparoscopy or videothoracoscopy are recommended for the diagnosis and repair of a missed diaphragmatic injury. The surgical repair with nonabsorbable simple sutures is adequate in most cases, and the use of mesh should be reserved for chronic and large defects.El diafragma es una estructura músculo-aponeurótica delgada y aplanada que separa la cavidad torácica de la abdominal. La hernia diafragmática traumática es una lesión poco frecuente y potencialmente mortal que puede presentarse en pacientes que han sufrido un traumatismo tóraco-abdominal tanto cerrado como penetrante. La ruptura diafragmática es un importante indicador de la gravedad del traumatismo. Suelen identificarse en el momento del traumatismo, pero en ocasiones pueden pasar desapercibidas y diagnosticarse meses, e incluso años, más tarde debido a la presencia de síntomas relacionados con las estructuras y órganos afectados. Si no se detecta a tiempo, la tasa de mortalidad puede aumentar debido a la aparición de graves complicaciones. El diagnóstico de la hernia diafragmática traumática es difícil y, a menudo, puede pasar desapercibido debido a la gravedad de las lesiones acompañantes. La radiografía de tórax en decúbito supino, a pesar de sus limitaciones, es el método de imagen más habitual y el más frecuentemente utilizado para evaluar los traumatismos torácicos. Sin embargo, la tomografía computarizada (TAC) es actualmente la exploración idónea y el principal método diagnóstico de las hernias diafragmáticas traumáticas. En pacientes hemodinámicamente estables la videolaparoscopia y la videotoracoscopia permiten el diagnóstico y en muchos casos el tratamiento de la lesión diafragmática. En la mayoría de los casos la sutura de los bordes de la herida diafragmática es suficiente para corregir la lesión. En los grandes defectos diafragmáticos puede ser necesario el uso de prótesis
Attracting complex networks
Real phenomena from different areas of Life Sciences can be described by complex networks, whose structure is usually determining their intrinsic dynamics. On the other hand, Dynamical Systems Theory is a powerful tool for the study of evolution processes in real situations. The concept of global attractor is the central one in this theory. In the last decades there has been an intensive research in the geometrical characterization of global attractors. However, there still exists a weak connection between the asymptotic dynamics of a complex network and the structure of associated global attractors. In this paper we show that, in order to analyze the long-time behavior of the dynamics on a complex network, it is the topological and geometrical structure of the attractor the subject to take into account. In fact,
given a complex network, a global attractor can be understood as the new attracting complex network which is really describing and determining the forwards dynamics of the phenomena. We illustrate our discussion with models of differential equations related to mutualistic complex networks in Economy and Ecology
An entropy test for single-locus genetic association analysis
<p>Abstract</p> <p>Background</p> <p>The etiology of complex diseases is due to the combination of genetic and environmental factors, usually many of them, and each with a small effect. The identification of these small-effect contributing factors is still a demanding task. Clearly, there is a need for more powerful tests of genetic association, and especially for the identification of rare effects</p> <p>Results</p> <p>We introduce a new genetic association test based on symbolic dynamics and symbolic entropy. Using a freely available software, we have applied this entropy test, and a conventional test, to simulated and real datasets, to illustrate the method and estimate type I error and power. We have also compared this new entropy test to the Fisher exact test for assessment of association with low-frequency SNPs. The entropy test is generally more powerful than the conventional test, and can be significantly more powerful when the genotypic test is applied to low allele-frequency markers. We have also shown that both the Fisher and Entropy methods are optimal to test for association with low-frequency SNPs (MAF around 1-5%), and both are conservative for very rare SNPs (MAF<1%)</p> <p>Conclusions</p> <p>We have developed a new, simple, consistent and powerful test to detect genetic association of biallelic/SNP markers in case-control data, by using symbolic dynamics and symbolic entropy as a measure of gene dependence. We also provide a standard asymptotic distribution of this test statistic. Given that the test is based on entropy measures, it avoids smoothed nonparametric estimation. The entropy test is generally as good or even more powerful than the conventional and Fisher tests. Furthermore, the entropy test is more computationally efficient than the Fisher's Exact test, especially for large number of markers. Therefore, this entropy-based test has the advantage of being optimal for most SNPs, regardless of their allele frequency (Minor Allele Frequency (MAF) between 1-50%). This property is quite beneficial, since many researchers tend to discard low allele-frequency SNPs from their analysis. Now they can apply the same statistical test of association to all SNPs in a single analysis., which can be especially helpful to detect rare effects.</p
Information Theory and Symbolic Analysis: Theory and Applications
Symbolic analysis has been developed and used successfully in very diverse fields [...
Algunas aportaciones de la teoría del caos al análisis empírico de series temporales
Tesis doctoral inédita. Universidad Autónoma de Madrid, Facultad de Ciencias Económicas y Empresariales, Departamento de Análisis Económico. Fecha de lectura: 31-05-02Bibliogr. : p. 211-22
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