969 resultados para Semi-parametric models


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2000 Mathematics Subject Classi cation: 62N01, 62N05, 62P10, 92D10, 92D30.

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We present a new approach to understand the landscape of supernova explosion energies, ejected nickel masses, and neutron star birth masses. In contrast to other recent parametric approaches, our model predicts the properties of neutrino-driven explosions based on the pre-collapse stellar structure without the need for hydrodynamic simulations. The model is based on physically motivated scaling laws and simple differential equations describing the shock propagation, the contraction of the neutron star, the neutrino emission, the heating conditions, and the explosion energetics. Using model parameters compatible with multi-D simulations and a fine grid of thousands of supernova progenitors, we obtain a variegated landscape of neutron star and black hole formation similar to other parametrized approaches and find good agreement with semi-empirical measures for the ‘explodability’ of massive stars. Our predicted explosion properties largely conform to observed correlations between the nickel mass and explosion energy. Accounting for the coexistence of outflows and downflows during the explosion phase, we naturally obtain a positive correlation between explosion energy and ejecta mass. These correlations are relatively robust against parameter variations, but our results suggest that there is considerable leeway in parametric models to widen or narrow the mass ranges for black hole and neutron star formation and to scale explosion energies up or down. Our model is currently limited to an all-or-nothing treatment of fallback and there remain some minor discrepancies between model predictions and observational constraints.

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Este documento evalúa el comportamiento de diferentes métodos (paramétrico, no paramétricos y semi-paramétricos) para estimar el VaR (valor en riesgo) de un portafolio representativo para 7 países latinoamericanos. El cálculo del VaR implica la estimación del i-esimo percentil de la distribución del valor futuro del valor de un portafolio. Los resultados no muestran la existencia de un método que se comporte mejor que los demás. Con un nivel de confianza del 95% los modelos paramétricos que emplean el EWMA se desempeñan en general bien así como con el TGARCH, pero estos modelos tienen un comportamiento pobre cuando la significancia considerada es del 1%.

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Essai doctoral présenté à la Faculté des études supérieures en vue de l'obtention du grade de Docteur en psychologie (D. Psy,), option clinique

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Essai doctoral présenté à la Faculté des études supérieures en vue de l'obtention du grade de Docteur en psychologie (D. Psy,), option clinique

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Survival models are being widely applied to the engineering field to model time-to-event data once censored data is here a common issue. Using parametric models or not, for the case of heterogeneous data, they may not always represent a good fit. The present study relays on critical pumps survival data where traditional parametric regression might be improved in order to obtain better approaches. Considering censored data and using an empiric method to split the data into two subgroups to give the possibility to fit separated models to our censored data, we’ve mixture two distinct distributions according a mixture-models approach. We have concluded that it is a good method to fit data that does not fit to a usual parametric distribution and achieve reliable parameters. A constant cumulative hazard rate policy was used as well to check optimum inspection times using the obtained model from the mixture-model, which could be a plus when comparing with the actual maintenance policies to check whether changes should be introduced or not.

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Recently semi-empirical models to estimate flow boiling heat transfer coefficient, saturated CHF and pressure drop in micro-scale channels have been proposed. Most of the models were developed based on elongated bubbles and annular flows in the view of the fact that these flow patterns are predominant in smaller channels. In these models, the liquid film thickness plays an important role and such a fact emphasizes that the accurate measurement of the liquid film thickness is a key point to validate them. On the other hand, several techniques have been successfully applied to measure liquid film thicknesses during condensation and evaporation under macro-scale conditions. However, although this subject has been targeted by several leading laboratories around the world, it seems that there is no conclusive result describing a successful technique capable of measuring dynamic liquid film thickness during evaporation inside micro-scale round channels. This work presents a comprehensive literature review of the methods used to measure liquid film thickness in macro- and micro-scale systems. The methods are described and the main difficulties related to their use in micro-scale systems are identified. Based on this discussion, the most promising methods to measure dynamic liquid film thickness in micro-scale channels are identified. (C) 2009 Elsevier Inc. All rights reserved.

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Although many mathematical models exist predicting the dynamics of transposable elements (TEs), there is a lack of available empirical data to validate these models and inherent assumptions. Genomes can provide a snapshot of several TE families in a single organism, and these could have their demographics inferred by coalescent analysis, allowing for the testing of theories on TE amplification dynamics. Using the available genomes of the mosquitoes Aedes aegypti and Anopheles gambiae, we indicate that such an approach is feasible. Our analysis follows four steps: (1) mining the two mosquito genomes currently available in search of TE families; (2) fitting, to selected families found in (1), a phylogeny tree under the general time-reversible (GTR) nucleotide substitution model with an uncorrelated lognormal (UCLN) relaxed clock and a nonparametric demographic model; (3) fitting a nonparametric coalescent model to the tree generated in (2); and (4) fitting parametric models motivated by ecological theories to the curve generated in (3).

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Survival analysis is applied when the time until the occurrence of an event is of interest. Such data are routinely collected in plant diseases, although applications of the method are uncommon. The objective of this study was to use two studies on post-harvest diseases of peaches, considering two harvests together and the existence of random effect shared by fruits of a same tree, in order to describe the main techniques in survival analysis. The nonparametric Kaplan-Meier method, the log-rank test and the semi-parametric Cox's proportional hazards model were used to estimate the effect of cultivars and the number of days after full bloom on the survival to the brown rot symptom and the instantaneous risk of expressing it in two consecutive harvests. The joint analysis with baseline effect, varying between harvests, and the confirmation of the tree effect as a grouping factor with random effect were appropriate to interpret the phenomenon (disease) evaluated and can be important tools to replace or complement the conventional analysis, respecting the nature of the variable and the phenomenon.

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Copyright © 2013 Springer Netherlands.

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Copyright 2013 Springer Netherlands.

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Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

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There is a vast literature that specifies Bayesian shrinkage priors for vector autoregressions (VARs) of possibly large dimensions. In this paper I argue that many of these priors are not appropriate for multi-country settings, which motivates me to develop priors for panel VARs (PVARs). The parametric and semi-parametric priors I suggest not only perform valuable shrinkage in large dimensions, but also allow for soft clustering of variables or countries which are homogeneous. I discuss the implications of these new priors for modelling interdependencies and heterogeneities among different countries in a panel VAR setting. Monte Carlo evidence and an empirical forecasting exercise show clear and important gains of the new priors compared to existing popular priors for VARs and PVARs.

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Drawing on PISA data of 2006, this study examines the impact of socio-economic school composition on science test score achievement for Spanish students in compulsory secondary schools. We define school composition in terms of the average parental human capital of students in the same school. These contextual peer effects are estimated using a semi-parametric methodology, which enables the spillovers to affect all the parameters of the educational production function. We also deal with the potential problem of self-selection of student into schools, using an artificial sorting that we argue to be independent from unobserved student’s abilities. The results indicate that the association between socio-economic school composition and test score results is clearly positive and significantly higher when computed with the semi-parametric approach. However, we find that the endogenous sorting of students into schools plays a fundamental role, given that the spillovers are significantly reduced when this selection process is ruled out from our measure of school composition effects. Specifically, the estimations suggest that the contextual peer effects are moderately positive only in those schools where the socio-economic composition is considerably elevated. In addition, we find some evidence of asymmetry of how the external effects and the sorting process actually operate, which seem affect in a different way males and females as well as high and low performance students.

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OBJECTIVES: To assess the extent to which stage at diagnosis and adherence to treatment guidelines may explain the persistent differences in colorectal cancer survival between the USA and Europe. DESIGN: A high-resolution study using detailed clinical data on Dukes' stage, diagnostic procedures, treatment and follow-up, collected directly from medical records by trained abstractors under a single protocol, with standardised quality control and central statistical analysis. SETTING AND PARTICIPANTS: 21 population-based registries in seven US states and nine European countries provided data for random samples comprising 12 523 adults (15-99 years) diagnosed with colorectal cancer during 1996-1998. OUTCOME MEASURES: Logistic regression models were used to compare adherence to 'standard care' in the USA and Europe. Net survival and excess risk of death were estimated with flexible parametric models. RESULTS: The proportion of Dukes' A and B tumours was similar in the USA and Europe, while that of Dukes' C was more frequent in the USA (38% vs 21%) and of Dukes' D more frequent in Europe (22% vs 10%). Resection with curative intent was more frequent in the USA (85% vs 75%). Elderly patients (75-99 years) were 70-90% less likely to receive radiotherapy and chemotherapy. Age-standardised 5-year net survival was similar in the USA (58%) and Northern and Western Europe (54-56%) and lowest in Eastern Europe (42%). The mean excess hazard up to 5 years after diagnosis was highest in Eastern Europe, especially among elderly patients and those with Dukes' D tumours. CONCLUSIONS: The wide differences in colorectal cancer survival between Europe and the USA in the late 1990s are probably attributable to earlier stage and more extensive use of surgery and adjuvant treatment in the USA. Elderly patients with colorectal cancer received surgery, chemotherapy or radiotherapy less often than younger patients, despite evidence that they could also have benefited.