913 resultados para multiple simultaneous equation models


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The first generation models of currency crises have often been criticized because they predict that, in the absence of very large triggering shocks, currency attacks should be predictable and lead to small devaluations. This paper shows that these features of first generation models are not robust to the inclusion of private information. In particular, this paper analyzes a generalization of the Krugman-Flood-Garber (KFG) model, which relaxes the assumption that all consumers are perfectly informed about the level of fundamentals. In this environment, the KFG equilibrium of zero devaluation is only one of many possible equilibria. In all the other equilibria, the lack of perfect information delays the attack on the currency past the point at which the shadow exchange rate equals the peg, giving rise to unpredictable and discrete devaluations.

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The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

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Experiments in which subjects play simultaneously several finite prisoner's dilemma supergames with and without an outside optionreveal that: (i) subjects use probabilistic start and endeffect behaviour, (ii) the freedom to choose whether to play the prisoner's dilemma game enhances cooperation, (iii) if the payoff for simultaneous defection is negative, subjects' tendency to avoid losses leads them to cooperate; while this tendency makes them stick to mutual defection if its payoff is positive.

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We consider an economy where the production technology has constantreturns to scale but where in the descentralized equilibrium thereare aggregate increasing returns to scale. The result follows froma positive contracting externality among firms. If a firms issurrounded by more firms, employees have more opportunitiesoutside their own firm. This improves employees' incentives toinvest in the presence of ex post renegotiation at the firm level,at not cost. Our leading result is that if a region is sparselypopulated or if the degree of development in the region is lowenough, there are multiple equilibria in the level of sectorialemployment. From the theoretical model we derive a non-linearfirst-order censored difference equation for sectoral employment.Our results are strongly consistent with the multiple equilibriahypothesis and the existence of a sectoral critical scale (belowwich the sector follows a delocation process). The scale of theregions' population and the degree of development reduce thecritical scale of the sector.

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n the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.

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Here I develop a model of a radiative-convective atmosphere with both radiative and convective schemes highly simplified. The atmospheric absorption of radiation at selective wavelengths makes use of constant mass absorption coefficients in finite width spectral bands. The convective regime is introduced by using a prescribed lapse rate in the troposphere. The main novelty of the radiative-convective model developed here is that it is solved without using any angular approximation for the radiation field. The solution obtained in the purely radiation mode (i. e. with convection ignored) leads to multiple equilibria of stable states, being very similar to some results recently found in simple models of planetary atmospheres. However, the introduction of convective processes removes the multiple equilibria of stable states. This shows the importance of taking convective processes into account even for qualitative analyses of planetary atmosphere

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Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

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Contamination of weather radar echoes by anomalous propagation (anaprop) mechanisms remains a serious issue in quality control of radar precipitation estimates. Although significant progress has been made identifying clutter due to anaprop there is no unique method that solves the question of data reliability without removing genuine data. The work described here relates to the development of a software application that uses a numerical weather prediction (NWP) model to obtain the temperature, humidity and pressure fields to calculate the three dimensional structure of the atmospheric refractive index structure, from which a physically based prediction of the incidence of clutter can be made. This technique can be used in conjunction with existing methods for clutter removal by modifying parameters of detectors or filters according to the physical evidence for anomalous propagation conditions. The parabolic equation method (PEM) is a well established technique for solving the equations for beam propagation in a non-uniformly stratified atmosphere, but although intrinsically very efficient, is not sufficiently fast to be practicable for near real-time modelling of clutter over the entire area observed by a typical weather radar. We demonstrate a fast hybrid PEM technique that is capable of providing acceptable results in conjunction with a high-resolution terrain elevation model, using a standard desktop personal computer. We discuss the performance of the method and approaches for the improvement of the model profiles in the lowest levels of the troposphere.

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In this paper we study the commuting and moving decisions of workers in Catalonia (Spain) and its evolution in the 1986-1996 period. Using a microdata sample from the 1991 Spanish Population Census, we estimate a simultaneous, discrete choice model of commuting and moves, thus indirectly addressing the home and job location decisions. The econometrical framework is a simultaneous, binary probit model with a commute equation and a move equation

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In this paper we study the commuting and moving decisions of workers in Catalonia (Spain) and its evolution in the 1986-1996 period. Using a microdata sample from the 1991 Spanish Population Census, we estimate a simultaneous, discrete choice model of commuting and moves, thus indirectly addressing the home and job location decisions. The econometrical framework is a simultaneous, binary probit model with a commute equation and a move equation

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Macroporosity is often used in the determination of soil compaction. Reduced macroporosity can lead to poor drainage, low root aeration and soil degradation. The aim of this study was to develop and test different models to estimate macro and microporosity efficiently, using multiple regression. Ten soils were selected within a large range of textures: sand (Sa) 0.07-0.84; silt 0.03-0.24; clay 0.13-0.78 kg kg-1 and subjected to three compaction levels (three bulk densities, BD). Two models with similar accuracy were selected, with a mean error of about 0.02 m³ m-3 (2 %). The model y = a + b.BD + c.Sa, named model 2, was selected for its simplicity to estimate Macro (Ma), Micro (Mi) or total porosity (TP): Ma = 0.693 - 0.465 BD + 0.212 Sa; Mi = 0.337 + 0.120 BD - 0.294 Sa; TP = 1.030 - 0.345 BD 0.082 Sa; porosity values were expressed in m³ m-3; BD in kg dm-3; and Sa in kg kg-1. The model was tested with 76 datum set of several other authors. An error of about 0.04 m³ m-3 (4 %) was observed. Simulations of variations in BD as a function of Sa are presented for Ma = 0 and Ma = 0.10 (10 %). The macroporosity equation was remodeled to obtain other compaction indexes: a) to simulate maximum bulk density (MBD) as a function of Sa (Equation 11), in agreement with literature data; b) to simulate relative bulk density (RBD) as a function of BD and Sa (Equation 13); c) another model to simulate RBD as a function of Ma and Sa (Equation 16), confirming the independence of this variable in relation to Sa for a fixed value of macroporosity and, also, proving the hypothesis of Hakansson & Lipiec that RBD = 0.87 corresponds approximately to 10 % macroporosity (Ma = 0.10 m³ m-3).

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OBJECTIVES: Lesion detection and characterization in multiple sclerosis (MS) are an essential part of its clinical diagnosis and an important research field. In this pilot study, we applied the recently introduced two inversion-contrast magnetization-prepared rapid gradient echo sequence (MP2RAGE) to patients with early-stage MS.¦MATERIALS AND METHODS: The MP2RAGE is a 3-dimensional (3D) magnetization-prepared rapid gradient echo derivative providing homogeneous T1 weighting and simultaneous T1 mapping. The MP2RAGE performance was compared with that of 2 clinical routine sequences (2D fluid-attenuated inversion recovery [FLAIR] and 3D magnetization-prepared rapid gradient echo [MP-RAGE]) and 2 state-of-the art clinical research sequences (the 3D FLAIR-SPACE [sampling perfection with application-optimized contrasts by using different flip-angle evolutions], a fluid-attenuated variable flip-angle fast spin echo technique, and the 3D double-inversion recovery SPACE). A cohort of 10 early-stage female MS patients (age, 31.6 ± 4.7 years; disease duration, 3.8 ± 1.9 years; median expanded disability status scale score, 1.75) and 10 age- and gender-matched controls were enrolled after approval of the local institutional review board was obtained. Multiple sclerosis lesions were identified and assigned to brain locations and tissue types by two experienced physicians in all 5 contrasts. Subsequently, lesions were manually delineated for comparison and statistical analysis of lesion count, volume and quantitative measures.¦RESULTS AND CONCLUSIONS: The results show that the 3D T1-weighted high-resolution MP2RAGE contrast provides a sensitive means for MS lesion assessment. The additional quantitative T1 relaxation time maps obtained with the MP2RAGE provide further potential diagnostic and prognostic information that could help (a) to better discriminate lesion subtypes and (b) to stage and predict the activity and the evolution of MS. Results also indicate that the T2-weighted double-inversion recovery and FLAIR-SPACE contrasts are attractive complements to the MP2RAGE for lesion detection.

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We derive nonlinear diffusion equations and equations containing corrections due to fluctuations for a coarse-grained concentration field. To deal with diffusion coefficients with an explicit dependence on the concentration values, we generalize the Van Kampen method of expansion of the master equation to field variables. We apply these results to the derivation of equations of phase-separation dynamics and interfacial growth instabilities.

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BACKGROUND: Whole pelvis intensity modulated radiotherapy (IMRT) is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB) to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. PURPOSE: To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB) regression and motion during chemo-radiotherapy (CRT) for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. METHODS AND MATERIALS: Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR) were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM) was used to evaluate the degree of motion. The Dice's similarity coefficient (DSC) was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. RESULTS: The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction between CTV-SIB reduction and OAR dose increase. CONCLUSIONS: The CTV-SIB had important regression and motion during CRT, receiving lower therapeutic doses than expected. The OAR had unpredictable shifts and received higher doses. The use of SIB without frequent adaptation of the treatment plan exposes cervical cancer patients to an unpredictable risk of under-dosing the target and/or overdosing adjacent critical structures. In that scenario, brachytherapy continues to be the gold standard approach.

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The oleaginous yeast Yarrowia lipolytica possesses six acyl-CoA oxidase (Aox) isoenzymes encoded by genes POX1-POX6. The respective roles of these multiple Aox isoenzymes were studied in recombinant Y. lipolytica strains that express heterologous polyhydroxyalkanoate (PHA) synthase (phaC) of Pseudomonas aeruginosa in varying POX genetic backgrounds, thus allowing assessment of the impact of specific Aox enzymes on the routing of carbon flow to β-oxidation or to PHA biosynthesis. Analysis of PHA production yields during growth on fatty acids with different chain lengths has revealed that the POX genotype significantly affects the PHA levels, but not the monomer composition of PHA. Aox3p function was found to be responsible for 90% and 75% of the total PHA produced from either C9:0 or C13:0 fatty acid, respectively, whereas Aox5p encodes the main Aox involved in the biosynthesis of 70% of PHA from C9:0 fatty acid. Other Aoxs, such as Aox1p, Aox2p, Aox4p and Aox6p, were not found to play a significant role in PHA biosynthesis, independent of the chain length of the fatty acid used. Finally, three known models of β-oxidation are discussed and it is shown that a 'leaky-hose pipe model' of the cycle can be applied to Y. lipolytica.