953 resultados para quasi-likelihood
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Let A be a unital dense algebra of linear mappings on a complex vector space X. Let φ = Σn i=1 Mai,bi be a locally quasi-nilpotent elementary operator of length n on A. We show that, if {a1, . . . , an} is locally linearly independent, then the local dimension of V (φ) = span{biaj : 1 ≤ i, j ≤ n} is at most n(n−1) 2 . If ldim V (φ) = n(n−1) 2 , then there exists a representation of φ as φ = Σn i=1 Mui,vi with viuj = 0 for i ≥ j. Moreover, we give a complete characterization of locally quasinilpotent elementary operators of length 3.
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No estudo de séries temporais, os processos estocásticos usuais assumem que as distribuições marginais são contínuas e, em geral, não são adequados para modelar séries de contagem, pois as suas características não lineares colocam alguns problemas estatísticos, principalmente na estimação dos parâmetros. Assim, investigou-se metodologias apropriadas de análise e modelação de séries com distribuições marginais discretas. Neste contexto, Al-Osh and Alzaid (1987) e McKenzie (1988) introduziram na literatura a classe dos modelos autorregressivos com valores inteiros não negativos, os processos INAR. Estes modelos têm sido frequentemente tratados em artigos científicos ao longo das últimas décadas, pois a sua importância nas aplicações em diversas áreas do conhecimento tem despertado um grande interesse no seu estudo. Neste trabalho, após uma breve revisão sobre séries temporais e os métodos clássicos para a sua análise, apresentamos os modelos autorregressivos de valores inteiros não negativos de primeira ordem INAR (1) e a sua extensão para uma ordem p, as suas propriedades e alguns métodos de estimação dos parâmetros nomeadamente, o método de Yule-Walker, o método de Mínimos Quadrados Condicionais (MQC), o método de Máxima Verosimilhança Condicional (MVC) e o método de Quase Máxima Verosimilhança (QMV). Apresentamos também um critério automático de seleção de ordem para modelos INAR, baseado no Critério de Informação de Akaike Corrigido, AICC, um dos critérios usados para determinar a ordem em modelos autorregressivos, AR. Finalmente, apresenta-se uma aplicação da metodologia dos modelos INAR em dados reais de contagem relativos aos setores dos transportes marítimos e atividades de seguros de Cabo Verde.
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La compréhension et la modélisation de l’interaction de l’onde électromagnétique avec la neige sont très importantes pour l’application des technologies radars à des domaines tels que l’hydrologie et la climatologie. En plus de dépendre des propriétés de la neige, le signal radar mesuré dépendra aussi des caractéristiques du capteur et du sol. La compréhension et la quantification des différents processus de diffusion du signal dans un couvert nival s’effectuent à travers les théories de diffusions de l’onde électromagnétique. La neige, dans certaines conditions, peut être considérée comme un milieu dense lorsque les particules de glace qui la composent y occupent une fraction volumique considérable. Dans un tel milieu, les processus de diffusion par les particules ne se font plus de façon indépendante, mais de façon cohérente. L’approximation quasi-cristalline pour les milieux denses est une des théories élaborées afin de prendre en compte ces processus de diffusions cohérents. Son apport a été démontré dans de nombreuses études pour des fréquences > 10 GHz où l’épaisseur optique de la neige est importante et où la diffusion de volume est prédominante. Par contre, les capteurs satellitaires radar présentement disponibles utilisent les bandes L (1-2GHz), C (4-8GHz) et X (8-12GHz), à des fréquences principalement en deçà des 10 GHz. L’objectif de la présente étude est d’évaluer l’apport du modèle de diffusion issu de l’approximation quasi-cristalline pour les milieux denses (QCA/DMRT) dans la modélisation de couverts de neige sèches en bandes C et X. L’approche utilisée consiste à comparer la modélisation de couverts de neige sèches sous QCA/DMRT à la modélisation indépendante sous l’approximation de Rayleigh. La zone d’étude consiste en deux sites localisés sur des milieux agricoles, près de Lévis au Québec. Au total 9 champs sont échantillonnés sur les deux sites afin d’effectuer la modélisation. Dans un premier temps, une analyse comparative des paramètres du transfert radiatif entre les deux modèles de diffusion a été effectuée. Pour des paramètres de cohésion inférieurs à 0,15 à des fractions volumiques entre 0,1 et 0,3, le modèle QCA/DMRT présentait des différences par rapport à Rayleigh. Un coefficient de cohésion optimal a ensuite été déterminé pour la modélisation d’un couvert nival en bandes C et X. L’optimisation de ce paramètre a permis de conclure qu’un paramètre de cohésion de 0,1 était optimal pour notre jeu de données. Cette très faible valeur de paramètre de cohésion entraîne une augmentation des coefficients de diffusion et d’extinction pour QCA/DMRT ainsi que des différences avec les paramètres de Rayleigh. Puis, une analyse de l’influence des caractéristiques du couvert nival sur les différentes contributions du signal est réalisée pour les 2 bandes C et X. En bande C, le modèle de Rayleigh permettait de considérer la neige comme étant transparente au signal à des angles d’incidence inférieurs à 35°. Vu l’augmentation de l’extinction du signal sous QCA/DMRT, le signal en provenance du sol est atténué d’au moins 5% sur l’ensemble des angles d’incidence, à de faibles fractions volumiques et fortes tailles de grains de neige, nous empêchant ainsi de considérer la transparence de la neige au signal micro-onde sous QCA/DMRT en bande C. En bande X, l’augmentation significative des coefficients de diffusion par rapport à la bande C, ne nous permet plus d’ignorer l’extinction du signal. La part occupée par la rétrodiffusion de volume peut dans certaines conditions, devenir la part prépondérante dans la rétrodiffusion totale. Pour terminer, les résultats de la modélisation de couverts de neige sous QCA/DMRT sont validés à l’aide de données RADARSAT-2 et TerraSAR-X. Les deux modèles présentaient des rétrodiffusions totales semblables qui concordaient bien avec les données RADARSAT-2 et TerraSAR-X. Pour RADARSAT-2, le RMSE du modèle QCA/DMRT est de 2,52 dB en HH et 2,92 dB en VV et pour Rayleigh il est de 2,64 dB en HH et 3,01 dB en VV. Pour ce qui est de TerraSAR-X, le RMSE du modèle QCA/DMRT allait de 1,88 dB en HH à 2,32 dB en VV et de 2,20 dB en HH à 2,71 dB en VV pour Rayleigh. Les valeurs de rétrodiffusion totales des deux modèles sont assez similaires. Par contre, les principales différences entre les deux modèles sont bien évidentes dans la répartition des différentes contributions de cette rétrodiffusion totale.
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Thesis (Ph.D.)--University of Washington, 2016-08
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There are two main aims of the paper. The first one is to extend the criterion for the precompactness of sets in Banach function spaces to the setting of quasi-Banach function spaces. The second one is to extend the criterion for the precompactness of sets in the Lebesgue spaces $L_p(\Rn)$, $1 \leq p < \infty$, to the so-called power quasi-Banach function spaces.
These criteria are applied to establish compact embeddings of abstract Besov spaces into quasi-Banach function spaces. The results are illustrated on embeddings of Besov spaces $B^s_{p,q}(\Rn)$, $0
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Research suggests that supervisors and peers can help employees make sense of what is important or expected from them at work and, thereby, shape their behaviors. In this dissertation, I examine how employees’ organizational citizenship behaviors (OCB), such as helping and voice, are differentially affected by these two sources of influence over time. In particular, I compare the relative and joint effectiveness of two field interventions to enhance OCB: (a) a role clarification intervention in which supervisors are trained to set expectations for OCB for their employees and encourage them to engage in OCB and (b) a norm establishment intervention in which peers are trained to set expectations for each other and encourage each other to perform OCB. I utilize a mixed methods approach involving a quasi-field experiment to test for changes in OCB and qualitative data to explore the theoretical mechanisms over the course of three months in a large food processing plant. I find that role clarification interventions alone have immediate positive effects on OCB, whereas norm establishment interventions alone take a longer period of time to increase OCB. In addition, in the condition where both interventions were combined, norm establishment interventions weaken the effects of role clarification earlier on; however, at later stages in time, this pattern reverses as norm establishment enhances the effects of role clarification on OCB. Through these findings, I highlight how (a) organizations seeking quick increases in citizenship might be better off focusing on supervisors as sources of influence; (b) organizations need to persist with peer-focused interventions to see positive gains; and (c) despite initial hurdles with peer-focused interventions, over time, they can lead to the highest increases in OCB when combined with supervisor-focused interventions.
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Hybrid logic is a valuable tool for specifying relational structures, at the same time that allows defining accessibility relations between states, it provides a way to nominate and make mention to what happens at each specific state. However, due to the many sources nowadays available, we may need to deal with contradictory information. This is the reason why we came with the idea of Quasi-hybrid logic, which is a paraconsistent version of hybrid logic capable of dealing with inconsistencies in the information, written as hybrid formulas. In [5] we have already developed a semantics for this paraconsistent logic. In this paper we go a step forward, namely we study its proof-theoretical aspects. We present a complete tableau system for Quasi-hybrid logic, by combining both tableaux for Quasi-classical and Hybrid logics.
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International audience
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Roads represent a new source of mortality due to animal-vehicle risk of collision threatening log-term populations’ viability. Risk of road-kill depends on species sensitivity to roads and their specific life-history traits. The risk of road mortality for each species depends on the characteristics of roads and bioecological characteristics of the species. In this study we intend to know the importance of climatic parameters (temperature and precipitation) together with traffic and life history traits and understand the role of drought in barn owl population viability, also affected by road mortality in three scenarios: high mobility, high population density and the combination of previous scenarios (mixed) (Manuscript). For the first objective we correlated the several parameters (climate, traffic and life history traits). We used the most correlated variables to build a predictive mixed model (GLMM) the influence of the same. Using a population model we evaluated barn owl population viability in all three scenarios. Model revealed precipitation, traffic and dispersal have negative relationship with road-kills, although the relationship was not significant. Scenarios showed different results, high mobility scenario showed greater population depletion, more fluctuations over time and greater risk of extinction. High population density scenario showed a more stable population with lower risk of extinction and mixed scenario showed similar results as first scenario. Climate seems to play an indirect role on barn owl road-kills, it may influence prey availability which influences barn owl reproductive success and activity. Also, high mobility scenario showed a greater negative impact on viability of populations which may affect their ability and resilience to other stochastic events. Future research should take in account climate and how it may influence species life cycles and activity periods for a more complete approach of road-kills. Also it is important to make the best mitigation decisions which might include improving prey quality habitat.
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We investigate numerically the nonlinear interactions between hetons. Hetons are baroclinic structures consisting of two vortices of opposite sign lying at different depths. Hetons are long-lived. They most often translate (they can sometimes rotate) and therefore they can noticeably contribute to the transport of scalar properties in the oceans. Heton interactions can interrupt this translation and thus this transport, by inducing a reconfiguration of interacting hetons into more complex baroclinic multipoles. More specifically, we study here the general case of two hetons, which collide with an offset between their translation axes. For this purpose, we use the point vortex theory, the ellipsoidal vortex model and direct simulations in the three-dimensional quasi-geostrophic contour surgery model. More specifically, this paper shows that there are in general three regimes for the interaction. For small horizontal offsets between the hetons, their vortices recombine as same-depth dipoles which escape at an angle. The angle depends in particular on the horizontal offset. It is a right angle for no offset, and the angle is shallower for small but finite offsets. The second limiting regime is for large horizontal offsets where the two hetons remain the same hetonic structures but are deflected by the weaker mutual interaction. Finally, the intermediate regime is for moderate offsets. This is the regime where the formation of a metastable quadrupole is possible. The formation of this quadrupole greatly restrains transport. Indeed, it constrains the vortices to reside in a closed area. It is shown that the formation of such structures is enhanced by the quasi-periodic deformation of the vortices. Indeed, these structures are nearly unobtainable for singular vortices (point vortices) but may be obtained using deformable, finite-core vortices.
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This paper deals with the development and the analysis of asymptotically stable and consistent schemes in the joint quasi-neutral and fluid limits for the collisional Vlasov-Poisson system. In these limits, the classical explicit schemes suffer from time step restrictions due to the small plasma period and Knudsen number. To solve this problem, we propose a new scheme stable for choices of time steps independent from the small scales dynamics and with comparable computational cost with respect to standard explicit schemes. In addition, this scheme reduces automatically to consistent discretizations of the underlying asymptotic systems. In this first work on this subject, we propose a first order in time scheme and we perform a relative linear stability analysis to deal with such problems. The framework we propose permits to extend this approach to high order schemes in the next future. We finally show the capability of the method in dealing with small scales through numerical experiments.
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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.
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We define Landau quasiparticles within the Gutzwiller variational theory and derive their dispersion relation for general multiband Hubbard models in the limit of large spatial dimensions D. Thereby we reproduce our previous calculations which were based on a phenomenological effective single-particle Hamiltonian. For the one-band Hubbard model we calculate the frst-order corrections in 1/D and find that the corrections to the quasiparticle dispersions are small in three dimensions. They may be largely absorbed in a rescaling of the total bandwidth, unless the system is close to half band filling. Therefore, the Gutzwiller theory in the limit of large dimensions provides quasiparticle bands which are suitable for a comparison with real, three-dimensional Fermi liquids.