Selection of the number of frequencies using bootstrap techniques in log-periodogram regression

The choice of the bandwidth in the local log-periodogram regression is of crucial importance for estimation of the memory parameter of a long memory time series. Different choices may give rise to completely different estimates, which may lead to contradictory conclusions, for example about the stationarity of the series. We propose here a data driven bandwidth selection strategy that is based on minimizing a bootstrap approximation of the mean squared error and compare its performance with other existing techniques for optimal bandwidth selection in a mean squared error sense, revealing its better performance in a wider class of models. The empirical applicability of the proposed strategy is shown with two examples: the widely analyzed in a long memory context Nile river annual minimum levels and the input gas rate series of Box and Jenkins.bootstrap, long memory, log-periodogram regression, bandwidth selection

Application of Semantics to Solve Problems in Life Sciences

Fecha de lectura de Tesis: 10 de diciembre de 2018La cantidad de información que se genera en la Web se ha incrementado en los últimos años. La mayor parte de esta información se encuentra accesible en texto, siendo el ser humano el principal usuario de la Web. Sin embargo, a pesar de todos los avances producidos en el área del procesamiento del lenguaje natural, los ordenadores tienen problemas para procesar esta información textual. En este cotexto, existen dominios de aplicación en los que se están publicando grandes cantidades de información disponible como datos estructurados como en el área de las Ciencias de la Vida. El análisis de estos datos es de vital importancia no sólo para el avance de la ciencia, sino para producir avances en el ámbito de la salud. Sin embargo, estos datos están localizados en diferentes repositorios y almacenados en diferentes formatos que hacen difícil su integración. En este contexto, el paradigma de los Datos Vinculados como una tecnología que incluye la aplicación de algunos estándares propuestos por la comunidad W3C tales como HTTP URIs, los estándares RDF y OWL. Haciendo uso de esta tecnología, se ha desarrollado esta tesis doctoral basada en cubrir los siguientes objetivos principales: 1) promover el uso de los datos vinculados por parte de la comunidad de usuarios del ámbito de las Ciencias de la Vida 2) facilitar el diseño de consultas SPARQL mediante el descubrimiento del modelo subyacente en los repositorios RDF 3) crear un entorno colaborativo que facilite el consumo de Datos Vinculados por usuarios finales, 4) desarrollar un algoritmo que, de forma automática, permita descubrir el modelo semántico en OWL de un repositorio RDF, 5) desarrollar una representación en OWL de ICD-10-CM llamada Dione que ofrezca una metodología automática para la clasificación de enfermedades de pacientes y su posterior validación haciendo uso de un razonador OWL

Optimizing a Simple Natural Dye Production Method for Dye-Sensitized Solar Cells: Examples for Betalain (Bougainvillea and Beetroot Extracts) and Anthocyanin Dyes

We present a study about the sensitizers extracted from natural resources. This paper focuses on how to select, extract and characterize natural dyes, giving some guides to establish a protocol for the whole process of fabricating and using these dyes. The influence of the extraction solvent and method, and of parameters such as pH are analyzed. Also, dye precursor and dye extract stability have been studied, as well as how the dye adsorbs onto substrates and the effect of mixing or concentrating the extracts. Results concerning betalain pigments present in bougainvillea and beetroot extracts, and anthocyanins in eggplant extracts, analyzed by using UV-Vis spectrometry, are included. As an example of application, we report procedures intended to test and enhance the dye potential as a main component of dye-sensitized solar cells (DSSCs). DSSCs mimic nature’s photosynthesis and have some advantages like an easy and low-cost fabrication procedure. Their efficiency depends on its design and fabrication process and also on the different components involved. Hence, optimizing each component is essential to achieve the best performance, and thus the dye used as a sensitizer is crucial. We fabricate cells by using a simple procedure: As the interest is focused on the sensitizer, the same consecutive steps are followed, varying only the dye extract. Among all the natural-dyes tested, beetroot extract reaches up to 0.47% cell efficiency, which is near the highest values found in literature for this pigment

Semiparametric inference in correlated long memory signal plus noise models

This paper proposes an extension of the log periodogram regression in perturbed long memory series that accounts for the added noise, also allowing for correlation between signal and noise, which represents a common situation in many economic and financial series. Consistency (for d < 1) and asymptotic normality (for d < 3/4) are shown with the same bandwidth restriction as required for the original log periodogram regression in a fully observable series, with the corresponding gain in asymptotic efficiency and faster convergence over competitors. Local Wald, Lagrange Multiplier and Hausman type tests of the hypothesis of no correlation between the latent signal and noise are also proposed.long memory, signal plus noise, semiparametric inference, log-periodogram regression

Gaussian Semiparametric Estimation in Long Memory in Stochastic Volatility and Signal Plus Noise Models

This paper considers the persistence found in the volatility of many financial time series by means of a local Long Memory in Stochastic Volatility model and analyzes the performance of the Gaussian semiparametric or local Whittle estimator of the memory parameter in a long memory signal plus noise model which includes the Long Memory in Stochastic Volatility as a particular case. It is proved that this estimate preserves the consistency and asymptotic normality encountered in observable long memory series and under milder conditions it is more efficient than the estimator based on a log-periodogram regression. Although the asymptotic properties do not depend on the signal-to-noise ratio the finite sample performance rely upon this magnitude and an appropriate choice of the bandwidth is important to minimize the influence of the added noise. I analyze the effect of the bandwidth via Monte Carlo. An application to a Spanish stock index is finally included.long memory, stochastic volatility, semiparametric estimation, frequency domain

Semiparametric estimation in perturbed long memory series

The estimation of the memory parameter in perturbed long memory series has recently attracted attention motivated especially by the strong persistence of the volatility in many financial and economic time series and the use of Long Memory in Stochastic Volatility (LMSV) processes to model such a behaviour. This paper discusses frequency domain semiparametric estimation of the memory parameter and proposes an extension of the log periodogram regression which explicitly accounts for the added noise, comparing it, asymptotically and in finite samples, with similar extant techniques. Contrary to the non linear log periodogram regression of Sun and Phillips (2003), we do not use a linear approximation of the logarithmic term which accounts for the added noise. A reduction of the asymptotic bias is achieved in this way and makes possible a faster convergence in long memory signal plus noise series by permitting a larger bandwidth. Monte Carlo results confirm the bias reduction but at the cost of a higher variability. An application to a series of returns of the Spanish Ibex35 stock index is finally included.long memory, stochastic volatility, semiparametric estimation

A predictive model of the export behaviour of small and medium sized firms: an applic.

Based on an extensive theoretical review, the aim of this paper is to carry out a closer examination of the differences between exporters according to their commitment to the international market. Once the main disparities are identified by means of a non-parametric test, a logistic analysis based upon data collected from small and medium sized manufacturing firms is conducted in order to construct a classificatory model.Export behaviour; Manufacturing; Small to medium-sized firms; Logistic regression; Ma

Further insights into exporter profiles: a classificatory model

One of the most relevant developments in the recent decades has been the progressive internationalisation of the world economy. To a great extent, physical borders have been removed by technological advancement, and this fact has made possible a rapprochement between countries and their respective cultures. For firms, this situation offers a range of possibilities owing to market increase. But, at the same time, domestic firms will have to face a rise in competition, and, probably, a market share decrease caused by the presence of foreign firms in their local market. Thus, to ensure survival, international expansion of firms’ activities becomes a necessity more than just an option. Despite this evidence, not all firms feel inclined to tackle their internationalisation process. Even between firms already sending their products abroad, it is possible to distinguish those ones that are fully engaged in export activity from those that just consider it an occasional task. That is to say, all exporters have neither the same international orientation, nor show the same export intensity. Consequently, grouping exporters in a single category could be misleading and could also hinder obtaining solid results in this research area. Furthermore, such a classification can counteract the efficiency of governmental export assistance programmes.The aim of this paper is to carry out a closer examination of the differences between active and passive exporters. With this purpose in mind, we first submit the considered variables to a non-parametric test in order to select those ones that better differentiate between both groups of exporters. Once the most relevant disparities are discovered, the significant variables are used to elaborate a classificatory model via a logistic function. The empirical analysis is based upon data collected from small and medium sized manufacturing firms located in Castilla-La Mancha, an inland region of Spain. The results indicate that a firm’s international experience and export intensity, and managers’ perceptions of foreign trade barriers are the most effective variables for distinguishing active from passive exporters. The obtained model accurately classifies 93% of cases. Finally, these findings allow us to formulate some policy recommendations that, probably, will increase the efficiency of export promotion expenditures.

Inappropriate use of proton-pump inhibitors and fragility fracture risk. A preliminary study

Introducción: Los inhibidores de la bomba de protones (IBP) son fármacos ampliamente utilizados, si bien esto conlleva a un sobreuso que no es acorde con las indicaciones aceptadas en España y en el resto de Europa. Por otro lado, algunos autores han establecido una posible implicación de los IBP en el riesgo de fractura. Con este trabajo hemos pretendido efectuar una primera aproximación al conocimiento del consumo de IBP en nuestro medio y analizar para qué indicación son prescritos, a la vez que estudiar su posible asociación con un mayor riesgo de fractura por fragilidad entre sus consumidores. Material y método: Estudio observacional, transversal, abierto, descriptivo, en el que se entrevistó aleatoriamente a un número de pacientes que fueron atendidos en diferentes ámbitos sanitarios: consultas externas hospitalarias, servicios de urgencias, consulta de Atención Primaria y pacientes ingresados en planta hospitalaria. Resultados: De los 411 pacientes entrevistados, el 54% de los pacientes recibían IBP, y cuya edad media era de 63,3 años, frente al 46% que no los tomaban y que eran más jóvenes, con una edad media de 50,9 años. La distribución por sexos fue similar. La principal razón de utilizar el IBP era como “protector gástrico”, en el 39,8% de los pacientes, indicación no existente en la ficha técnica de este grupo de fármacos. Los consumidores de IBP tenían una mayor prevalencia de todas las fracturas por fragilidad. Conclusiones: Más de la mitad de la población encuestada consume IBP, y de ella cerca del 40% sin una indicación médica correcta. Por esto, unido a la mayor prevalencia de fracturas por fragilidad que presentan –que nos hace pensar en un posible mayor riesgo de fractura entre sus usuarios– consideramos la necesidad de un uso más racional de estos fármacos. Estas conclusiones son preliminares pero, a la vista de estos resultados, creemos que puede ser interesante realizar más estudios dirigidos a comprobar de manera más firme la relación entre los IBP y el riesgo de fractura osteoporótica.Sociedad Canaria de Osteoporosi