938 resultados para General Linear Model


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Ein neu entwickeltes globales Atmosphärenchemie- und Zirkulationsmodell (ECHAM5/MESSy1) wurde verwendet um die Chemie und den Transport von Ozonvorläufersubstanzen zu untersuchen, mit dem Schwerpunkt auf Nichtmethankohlenwasserstoffen. Zu diesem Zweck wurde das Modell durch den Vergleich der Ergebnisse mit Messungen verschiedenen Ursprungs umfangreich evaluiert. Die Analyse zeigt, daß das Modell die Verteilung von Ozon realistisch vorhersagt, und zwar sowohl die Menge als auch den Jahresgang. An der Tropopause gibt das Modell den Austausch zwischen Stratosphäre und Troposphäre ohne vorgeschriebene Flüsse oder Konzentrationen richtig wieder. Das Modell simuliert die Ozonvorläufersubstanzen mit verschiedener Qualität im Vergleich zu den Messungen. Obwohl die Alkane vom Modell gut wiedergeben werden, ergibt sich einige Abweichungen für die Alkene. Von den oxidierten Substanzen wird Formaldehyd (HCHO) richtig wiedergegeben, während die Korrelationen zwischen Beobachtungen und Modellergebnissen für Methanol (CH3OH) und Aceton (CH3COCH3) weitaus schlechter ausfallen. Um die Qualität des Modells im Bezug auf oxidierte Substanzen zu verbessern, wurden einige Sensitivitätsstudien durchgeführt. Diese Substanzen werden durch Emissionen/Deposition von/in den Ozean beeinflußt, und die Kenntnis über den Gasaustausch mit dem Ozean ist mit großen Unsicherheiten behaftet. Um die Ergebnisse des Modells ECHAM5/MESSy1 zu verbessern wurde das neue Submodell AIRSEA entwickelt und in die MESSy-Struktur integriert. Dieses Submodell berücksichtigt den Gasaustausch zwischen Ozean und Atmosphäre einschließlich der oxidierten Substanzen. AIRSEA, welches Informationen über die Flüssigphasenkonzentration des Gases im Oberflächenwasser des Ozeans benötigt wurde ausgiebig getestet. Die Anwendung des neuen Submodells verbessert geringfügig die Modellergebnisse für Aceton und Methanol, obwohl die Verwendung einer vorgeschriebenen Flüssigphasenkonzentration stark den Erfolg der Methode einschränkt, da Meßergebnisse nicht in ausreichendem Maße zu Verfügung stehen. Diese Arbeit vermittelt neue Einsichten über organische Substanzen. Sie stellt die Wichtigkeit der Kopplung zwischen Ozean und Atmosphäre für die Budgets vieler Gase heraus.

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Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed modesl and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated marginal residual vector by the Cholesky decomposition of the inverse of the estimated marginal variance matrix. Linear functions or the resulting "rotated" residuals are used to construct an empirical cumulative distribution function (ECDF), whose stochastic limit is characterized. We describe a resampling technique that serves as a computationally efficient parametric bootstrap for generating representatives of the stochastic limit of the ECDF. Through functionals, such representatives are used to construct global tests for the hypothesis of normal margional errors. In addition, we demonstrate that the ECDF of the predicted random effects, as described by Lange and Ryan (1989), can be formulated as a special case of our approach. Thus, our method supports both omnibus and directed tests. Our method works well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series).

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Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed models and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated margional residual vector by the Cholesky decomposition of the inverse of the estimated margional variance matrix. The resulting "rotated" residuals are used to construct an empirical cumulative distribution function and pointwise standard errors. The theoretical framework, including conditions and asymptotic properties, involves technical details that are motivated by Lange and Ryan (1989), Pierce (1982), and Randles (1982). Our method appears to work well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series). Our methods can produce satisfactory results even for models that do not satisfy all of the technical conditions stated in our theory.

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Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model, normal base measures and Gibbs sampling procedures based on the Pólya urn scheme are often used to simulate posterior draws. These algorithms are applicable in the conjugate case when (for a normal base measure) the likelihood is normal. In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998) and Neal (2000) are often applied to generate posterior samples. Some common problems associated with simulation algorithms for non-conjugate MDP models include convergence and mixing difficulties. This paper proposes an algorithm based on the Pólya urn scheme that extends the Gibbs sampling algorithms to non-conjugate models with normal base measures and exponential family likelihoods. The algorithm proceeds by making Laplace approximations to the likelihood function, thereby reducing the procedure to that of conjugate normal MDP models. To ensure the validity of the stationary distribution in the non-conjugate case, the proposals are accepted or rejected by a Metropolis-Hastings step. In the special case where the data are normally distributed, the algorithm is identical to the Gibbs sampler.

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In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

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This paper explores the potential usefulness of an AGE model with the Melitz-type trade specification to assess economic effects of technical regulations, taking the case of the EU ELV/RoHS directives as an example. Simulation experiments reveal that: (1) raising the fixed exporting cost to make sales in the EU market brings results that exports of the targeted commodities (motor vehicles and parts for ELV and electronic equipment for RoHS) to the EU from outside regions/countries expand while the domestic trade in the EU shrinks when the importer's preference for variety (PfV) is not strong; (2) if the PfV is not strong, policy changes that may bring reduction in the number of firms enable survived producers with high productivity to expand production to be large-scale mass producers fully enjoying the fruit of economies of scale; and (3) When the strength of the importer's PfV is changed from zero to unity, there is the value that totally changes simulation results and their interpretations.

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The ECHAM-1 T21/LSG coupled ocean-atmosphere general circulation model (GCM) is used to simulate climatic conditions at the last interglacial maximum (Eemian. 125 kyr BP). The results reflect thc expected surface temperature changes (with respect to the control run) due to the amplification (reduction) of the seasonal cycle of insolation in the Northern (Southern) Hemisphere. A number of simulated features agree with previous results from atmospheric GCM simulations e.g. intensified summer southwest monsoons) except in the Northern Hemisphere poleward of 30 degrees N. where dynamical feedback, in the North Atlantic and North Pacific increase zonal temperatures about 1 degrees C above what would be predicted from simple energy balance considerations. As this is the same area where most of the terrestrial geological data originate, this result suggests that previous estimates of Eemian global average temperature might have been biased by sample distribution. This conclusion is supported by the fact that the estimated global temperature increase of only 0.3 degrees C greater than the control run ha, been previously shown to be consistent a with CLIMAP sea surface temperature estimates. Although the Northern Hemisphere summer monsoon is intensified. globally averaged precipitation over land is within about 1% of the present, contravening some geological inferences bur not the deep-sea delta(13)C estimates of terrestrial carbon storage changes. Winter circulation changes in the northern Arabian Sea. driven by strong cooling on land, are as large as summer circulation changes that are the usual focus of interest, suggesting that interpreting variations in the Arabian Sea. sedimentary record solely in terms of the summer monsoon response could sometimes lead to errors. A small monsoonal response over northern South America suggests that interglacial paleotrends in this region were not just due to El Nino variations.

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Senior thesis written for Oceanography 445

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BACKGROUND: Regional differences in physician supply can be found in many health care systems, regardless of their organizational and financial structure. A theoretical model is developed for the physicians' decision on office allocation, covering demand-side factors and a consumption time function. METHODS: To test the propositions following the theoretical model, generalized linear models were estimated to explain differences in 412 German districts. Various factors found in the literature were included to control for physicians' regional preferences. RESULTS: Evidence in favor of the first three propositions of the theoretical model could be found. Specialists show a stronger association to higher populated districts than GPs. Although indicators for regional preferences are significantly correlated with physician density, their coefficients are not as high as population density. CONCLUSIONS: If regional disparities should be addressed by political actions, the focus should be to counteract those parameters representing physicians' preferences in over- and undersupplied regions.

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Macroeconomic policy makers are typically concerned with several indicators of economic performance. We thus propose to tackle the design of macroeconomic policy using Multicriteria Decision Making (MCDM) techniques. More specifically, we employ Multiobjective Programming (MP) to seek so-called efficient policies. The MP approach is combined with a computable general equilibrium (CGE) model. We chose use of a CGE model since they have the dual advantage of being consistent with standard economic theory while allowing one to measure the effect(s) of a specific policy with real data. Applying the proposed methodology to Spain (via the 1995 Social Accounting Matrix) we first quantified the trade-offs between two specific policy objectives: growth and inflation, when designing fiscal policy. We then constructed a frontier of efficient policies involving real growth and inflation. In doing so, we found that policy in 1995 Spain displayed some degree of inefficiency with respect to these two policy objectives. We then offer two sets of policy recommendations that, ostensibly, could have helped Spain at the time. The first deals with efficiency independent of the importance given to both growth and inflation by policy makers (we label this set: general policy recommendations). A second set depends on which policy objective is seen as more important by policy makers: increasing growth or controlling inflation (we label this one: objective-specific recommendations).