939 resultados para parameter driven model
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In this study, a mathematical model for the production of Fructo-oligosaccharides (FOS) by Aureobasidium pullulans is developed. This model contains a relatively large set of unknown parameters, and the identification problem is analyzed using simulation data, as well as experimental data. Batch experiments were not sufficiently informative to uniquely estimate all the unknown parameters, thus, additional experiments have to be achieved in fed-batch mode to supplement the missing information. © 2015 IEEE.
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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)
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Telecommunications and network technology is now the driving force that ensures continued progress of world civilization. Design of new and expansion of existing network infrastructures requires improving the quality of service(QoS). Modeling probabilistic and time characteristics of telecommunication systems is an integral part of modern algorithms of administration of quality of service. At present, for the assessment of quality parameters except simulation models analytical models in the form of systems and queuing networks are widely used. Because of the limited mathematical tools of models of these classes the corresponding parameter estimation of parameters of quality of service are inadequate by definition. Especially concerning the models of telecommunication systems with packet transmission of multimedia real-time traffic.
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The purpose of the research is the creation of mathematical models in MATLAB based on the double exponential model of the photovoltaic cell. The developed model allows for different physical and environmental parameters. An equivalent circuit of the model includes a photocurrent source, two diodes, and a series and parallel resistance. The paper presents the simulation results for each parameter. The simulation data are displayed graphically and numerical results are saved in a file.
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This study has aims to determine the age and to estimate the growth parameters using scales of the species. Individuals of Piaractus mesopotamicus (Holmberg, 1887) used in this study were captured in the commercial fishery conducted in the region, along the year 2006. The model selected to express the growth of the species was the von Bertalanffy Sl= Sl∞*[1-exp-k(t-to)]. To determine if scales are suitable for studying the growth of pacu, we analyzed the relation between standard length (Sl) and the radius of the scales through linear regression. The period of annuli formation was determined analyzing the variations in the marginal increment and evaluating the consistency of the readings through the analysis of the coefficient of variations (CVs) for the average standard lengths of each age (number of rings) observed in the scales. The relationship between Ls of the fish and the radius of the scales showed that scales can be used to study the age and growth of P. mesopotamicus (R= 0.79). CVs were always below 20%, demonstrating the consistency of the readings. Annuli formation occurred in February, probably related to trophic migration that occurs in this month in the region. Equations that represents the growth in length obtained for P. mesopotamicus are Sl=50.00*[1-exp-0.18(t-(-3.00)] for males and Sl=59.23*[1-exp-0.14(t-(-3.36)] for females. The growth parameters obtained in this study were lower compared to other studies previously conducted for the same species and can related to overexploitation that species is submitted by fishing in the region. These values show also that females of pacu attain greater asymptotic length than males that growth faster.
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There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.
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Paper delivered at the Western Regional Science Association Annual Conference, Sedona, Arizona, February, 2010.
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Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.
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In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.
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This paper examines whether efficiency considerations require that optimal labour income taxation is progressive or regressive in a model with skill heterogeneity, endogenous skill acquisition and a production sector with capital-skill complementarity. We find that wage inequality driven by the resource requirements of skill-creation implies progressive labour income taxation in the steady-state as well as along the transition path from the exogenous to optimal policy steady-state. We find that these results are explained by a lower labour supply elasticity for skilled versus unskilled labour which results from the introduction of the skill acquisition technology.
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Asynchronous exponential growth has been extensively studied in population dynamics. In this paper we find out the asymptotic behaviour in a non-linear age-dependent model which takes into account sexual reproduction interactions. The main feature of our model is that the non-linear process converges to a linear one as the solution becomes large, so that the population undergoes asynchronous growth. The steady states analysis and the corresponding stability analysis are completely made and are summarized in a bifurcation diagram according to the parameter R0. Furthermore the effect of intraspecific competition is taken into account, leading to complex dynamics around steady states.
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This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and volatilities, and our model averaging method allows for investors' model uncertainty over time. Our time-varying parameter Nelson-Siegel Dynamic Model Averaging (NS-DMA) predicts yields better than standard benchmarks and successfully captures plausible time-varying term premia in real time. The proposed model has significant in-sample and out-of-sample predictability for excess bond returns, and the predictability is of economic value.
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Among the various work stress models, one of the most popular to date is the job demands-‐control (JDC) model developed by Karasek (1979), which postulates that work-‐related strain will be the highest under work conditions characterized by high demands and low autonomy. The absence of social support at work will further increase negative outcomes. However, this model does not apply equally to all individuals and to all cultures. In the following studies, we assessed work characteristics, personality traits, culture-‐driven individual attributes, and work-‐related health outcomes, through the administration of questionnaires. The samples consist of Swiss (n = 622) and South African (n = 879) service-‐oriented employees (from health, finance, education and commerce sectors) and aged from 18 to 65 years old. Results generally confirm the universal contribution of high psychological demands, low decision latitude and low supervisor support at work, as well as high neuroticism predict the worse health outcomes among employees in both countries. Furthermore, low neuroticism plays a moderating role between psychological demands and burnout, while high openness and high conscientiousness each play a moderating role between decision latitude and burnout in South Africa. Results also reveal that culture-‐driven individual attributes play a role in both countries, but in a unique manner and according to the ethnic group of belonging. Given that organizations are increasingly characterized with multicultural employees as well as increasingly adverse and complex job conditions, our results help in identifying more updated and refined dynamics that are key between the employee and the work environment in today's context. -- L'un des modèles sur le stress au travail des plus répandus est celui développé par Karasek (1979), qui postule qu'une mauvaise santé chez les employés résulte d'une combinaison de demandes psychologiques élevées, d'une latitude décisionnelle faible et de l'absence de soutien social au travail. Néanmoins, ce modèle ne s'applique pas de façon équivalente chez tous les individus et dans toutes les cultures. Dans les études présentées, nous avons mesuré les caractéristiques de travail, les traits de personnalité, les traits culturels et les effets lies à la santé à l'aide de questionnaires. L'échantillon provient de la Suisse (n = 622) et de l'Afrique du Sud (n = 879) et comprend des employés de domaines divers en lien avec le service (notamment des secteurs de la santé, finance, éducation et commerce) tous âgés entre 18 et 65 ans. Les résultats confirment l'universalité des effets directs des demandes au travail, la latitude décisionnelle faible, le soutien social faible provenant du supérieur hiérarchique, ainsi que le névrosisme élevé qui contribuent à un niveau de santé faible au travail, et ce, dans les deux pays. De plus, un niveau faible de névrosisme a un effet de modération entre les demandes au travail et l'épuisement professionnel, alors que l'ouverture élevée et le caractère consciencieux élevé modèrent la relation entre la latitude décisionnelle et l'épuisement professionnel en Afrique du Sud. Nous avons aussi trouvé que les traits culturels jouent un rôle dans les deux pays, mais de façon unique et en fonction du groupe ethnique d'appartenance. Sachant que les organisations sont de plus en plus caractérisées par des employés d'origine ethnique variées, et que les conditions de travail se complexifient, nos résultats contribuent à mieux comprendre les dynamiques entre l'employé et l'environnement de travail contemporain. personnalité, différences individuelles, comparaisons culturelles, culture, stress au travail, épuisement professionnel, santé des employés.
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BACKGROUND: Humanized murine models comprise a new tool to analyze novel therapeutic strategies for allergic diseases of the intestine.¦OBJECTIVE: In this study we developed a human PBMC-engrafted murine model of allergen-driven gut inflammation and analyzed the underlying immunologic mechanisms.¦METHODS: Nonobese diabetic (NOD)-scid-γc(-/-) mice were injected intraperitoneally with human PBMCs from allergic donors together with the respective allergen or not. Three weeks later, mice were challenged with the allergen orally or rectally, and gut inflammation was monitored with a high-resolution video miniendoscopic system, as well as histologically.¦RESULTS: Using the aeroallergens birch or grass pollen as model allergens and, for some donors, also hazelnut allergen, we show that allergen-specific human IgE in murine sera and allergen-specific proliferation and cytokine production of human CD4(+) T cells recovered from spleens after 3 weeks could only be measured in mice treated with PBMCs plus allergen. Importantly, these mice had the highest endoscopic scores evaluating translucent structure, granularity, fibrin, vascularity, and stool after oral or rectal allergen challenge and a strong histologic inflammation of the colon. Analyzing the underlying mechanisms, we demonstrate that allergen-associated colitis was dependent on IgE, human IgE receptor-expressing effector cells, and the mediators histamine and platelet-activating factor.¦CONCLUSION: These results demonstrate that allergic gut inflammation can be induced in human PBMC-engrafted mice, allowing the investigation of pathophysiologic mechanisms of allergic diseases of the intestine and evaluation of therapeutic interventions.
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It has been argued that by truncating the sample space of the negative binomial and of the inverse Gaussian-Poisson mixture models at zero, one is allowed to extend the parameter space of the model. Here that is proved to be the case for the more general three parameter Tweedie-Poisson mixture model. It is also proved that the distributions in the extended part of the parameter space are not the zero truncation of mixed poisson distributions and that, other than for the negative binomial, they are not mixtures of zero truncated Poisson distributions either. By extending the parameter space one can improve the fit when the frequency of one is larger and the right tail is heavier than is allowed by the unextended model. Considering the extended model also allows one to use the basic maximum likelihood based inference tools when parameter estimates fall in the extended part of the parameter space, and hence when the m.l.e. does not exist under the unextended model. This extended truncated Tweedie-Poisson model is proved to be useful in the analysis of words and species frequency count data.