1,142 research outputs found
An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test
This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.This research has been partially supported by the Spanish Consejería de Economía, Innovación y Ciencia of the Junta de Andalucía under projects TIC-6441 and P11-RNM7115, and the Spanish MEC under project ECO2011–29751
Alpha-dense curves in infinite dimensional spaces
The theory of α−dense curves in the euclidean space Rn , n ≥ 2, was developed for finding algorithms for Global Optimization of multivariable functions ([1], [6]). The α-dense curves, considered as a generalization of Peano curves or space-filling curves, densify the domain of definition D of a multivariable function f in the sense of the Hausdorff metric. Then, the restriction of f on an α−dense curve γ, contained in D, is a univariable function fγ for which will have less difficulty to locate its global minimum. In this paper we shall study some properties of α−dense curves that are Lipschitzian. Moreover, we shall point out that this theory of α−dense curves is characteristic of the finite dimensional spaces. In fact, we shall prove that a Banach space has finite dimension iff its unit ball can be densified with arbitrary small density α. From this, we shall deduce the classical Theorem of Riesz. Finally, we shall construct a family of infinite dimensional α−dense curves, whith controlled density α, in the Hilbert parallelotope
Improving the structural reliability of steel frames using posttensioned connections
In this paper, various moment-resisting steel frames (MRSFs) are subjected to 30 narrow-band motions scaled at different ground motion intensity levels in terms of spectral acceleration at first mode of vibration in order to perform incremental dynamic analysis for peak and residual interstory drift demands. The results are used to compute the structural reliability of the steel frames by means of hazard curves for peak and residual drifts. It is observed that the structures exceed the threshold residual drift of 0.5%, which is perceptible to human occupants, and it could lead to human discomfort according to recent investigations. For this reason, posttensioned connections (PTCs) are incorporated into the steel frames in order to improve the structural reliability. The results suggest that the annual rate of exceedance of peak and residual interstory drift demands are reduced with the use of PTC. Thus, the structural reliability of the steel frames with PTC is superior to that of the MRSFs. In particular, the residual drift demands tend to be smaller when PTCs are incorporated in the steel structures.Peer ReviewedPostprint (published version
Cooperación técnica : una propuesta para la asociación internacional de aseguradores de depósitos
Con el fin de proponer una política de cooperación técnica para la Asociación Internacional de Aseguradores de Depósitos (IADI, por su sigla en inglés), se desarrolló una encuesta entre sus miembros con el fin de determinar las necesidades de cooperación técnica relacionadas con el cumplimiento de los Principios Básicos para Aseguradores de Depósitos Eficaces. A partir de este insumo se realizó un análisis de componentes principales, el cual arrojó que: i) las necesidades de cooperación pueden ser agrupadas con base en el mandato de los aseguradores de depósitos, ii) existen cinco componentes que representan cerca del 70% de la variabilidad de las variables identificadas, y iii) hay incidencia de características institucionales en la realización de solicitudes de cooperación técnica. De esta forma, el modelo le permitiría a la IADI contar con las herramientas para desarrollar un programa de cooperación desde un demand-sided approach, en línea con las mejores prácticas internacionales.Resumen. Problema de investigación. Preguntas de investigación. HipótesiS. Objetivos. Marco teórico. Estado del arte. Estándares internacionales para la resolución de entidades financieras y aseguradores de depósitos. Los seguros de depósitos: características y estado actual. Cooperación internacional: evolución y prácticas actuales. Metodología. Encuesta sobre necesidades de cooperación técnica de los miembros de la IADI. Clasificación de las solicitudes por tipo de mandato. Clasificación de las solicitudes por región geográfica. Análisis de componentes principales. Construcción de índices a partir del análisis de componentes principales. Implicaciones de política. ConclusiónMagíster en Administración de EmpresasMaestrí
Estimating Value-at-Risk and Expected Shortfall: Do Polynomial Expansions Outperform Parametric Densities?
We assess Value-at-Risk (VaR) and Expected Shortfall (ES) estimates assuming different models for the standardized returns: distributions based on polynomial expansions such as Cornish-Fisher and Gram-Charlier, and well-known parametric densities such as normal, skewed-t and Johnson. This paper aims to analyze whether models based on polynomial expansions outperform the parametric ones. We carry out the model performance comparison in two stages: first, with a backtesting analysis of VaR and ES; and second, using loss functions. Our backtesting results show that all distributions, except for normal ones, perform quite well in VaR and ES estimations. Regarding the loss function analysis, we conclude that polynomial expansions (specifically, the Cornish-Fisher one) usually outperform parametric densities in VaR estimation, but the latter (specifically, the Johnson density) slightly outperform the former in ES estimation; however, the gains of using one approach or the other are modest.This paper has been supported by Spanish Government under project PID2021-124860NB-I00 and Generalitat Valenciana under project CIPROM/2021/060
Counterfactual distributions of wages via quantile regression with endogeneity
Counterfactual decompositions allow the researcher to analyze the changes in wage distributions by discriminating between the effect of changes in the population characteristics and the effect of changes in returns to these characteristics. In this paper, counterfactual distributions are derived by recovering the conditional distribution via a set of quantile regressions, and correcting for the endogeneity of schooling decisions using a control function approach. Our proposal enables us to isolate the effect on the wage distribution of changes in both the conditional and unconditional distribution of schooling and changes in the distribution of unobserved ability. This methodology is used to analyze the sources of the changes in wage distribution that took place in the United States between 1983 and 1993, using proximity to college for different parental background as instruments. Our results show that the change in the distribution of ability had a negative effect on wages at the low quantiles, which almost compensates the positive effect of the change in the schooling distribution over this period. It is also found that the impact on wages of changes in the conditional distribution of unobserved ability is larger than the impact of changes in the conditional distribution of distance to college.Counterfactual Decomposition, Wage Inequality, Quantile Regression, Endogeneity
Perceived attachment and problematic smartphone use in young people: mediating effects of self-regulation and prosociality
Background: Problematic use of smartphones is a challenge facing societies around the world. This phenomenon has been associated with negative socialization experiences through the impact they have on how the youth relates to their environment. This study was designed to examine parental and peer attachment, self-efficacy and prosocial reasoning as predictors of different attitudes towards online communication and problematic smartphone use. Method: 561 youth aged 14-20 years (Mage= 17.82; SD= 1.64; 67.7% Female) participated in an online survey. Results: Results indicated that an increase in self-efficacy or prosocial reasoning is correlated with a decrease in problematic smartphone use and attitudes towards online communication aimed at avoiding reality or constructing a more comfortable parallel social reality. Attachment to parents and peers had direct and indirect effects on problematic smartphone use and attitudes toward online communication through youth personal and social adjustment. Conclusions: Attachment plays a relevant role in the symptoms reduction of smartphone addiction and attitudes to online communication in youth, through its impact on self-efficacy perceptions and prosocial reasoning
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