998 resultados para stochastic methods


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We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.

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We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.

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This paper uses sequential stochastic dominance procedures to compare the joint distribution of health and income across space and time. It is the First application of which we are aware of methods to compare multidimensional distributions of income and health using procedures that are robust to aggregation techniques. The paper's approach is more general than comparisons of health gradients and does not require the estimation of health equivalent incomes. We illustrate the approach by contrasting Canada and the US using comparable data. Canada dominates the US over the lower bidimensional welfare distribution of health and income, though not generally in terms of the uni-dimensional distribution of health or income. The paper also finds that welfare for both Canadians and Americans has not unambiguously improved during the last decade over the joint distribution of income and health, in spite of the fact that the uni-dimensional distributions of income have clearly improved during that period.

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Classical definitions of complementarity are based on cross price elasticities, and so they do not apply, for example, when goods are free. This context includes many relevant cases such as online newspapers and public attractions. We look for a complementarity notion that does not rely on price variation and that is: behavioural (based only on observable choice data); and model-free (valid whether the agent is rational or not). We uncover a conflict between properties that complementarity should intuitively possess. We discuss three ways out of the impossibility.

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This paper uses data on the world's copper mining industry to measure the impact on efficiency of the adoption of the ISO 14001 environmental standard. Anecdotal and case study literature suggests that firms are motivated to adopt this standard so as to achieve greater efficiency through changes in operating procedures and processes. Using plant level panel data from 1992-2007 on most of the world's industrial copper mines, the study uses stochastic frontier methods to investigate the effects of ISO adoption. The variety of models used in this study find that adoption either tends to improve efficiency or has no impact on efficiency, but no evidence is found that ISO adoption decreases efficiency.

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Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.

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Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

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The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate.

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The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

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Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

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The diagnosis of tick-borne diseases such as babesiosis still depends on observing the parasite in the infected erythrocyte. Microscopic observation is tedious and often problematic in both early and carrier infections. Better diagnostic methods are needed to prevent clinical disease, especially when susceptible cattle are being moved into disease enzootic areas. This study evaluates two techniques for early diagnosis of Babesia bovis infections in cattle, DNA probes specific for the organism and fluorescent probes specific nucleic acid. The radioisotopically labeled DNA probes are used in slot blot hybridizations whith lysed blood samples, not purified DNA. Thusfar, the probe is specific for B. bovis and can detect as few as 1000 B. bovis parasites in 10µl of blood. The specificity of the fluorescent probe depends on the characteristic morphology of the babesia in whole blood samples, as determined microscopically. The fluorescent probe detects as afew as 10,000 B. bovis parasites in 10*l as blood. The application of each method for alboratory and field use is discussed.

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Accurate diagnosis of Babesia bigemina infection, an economically important tick-transmitted protozoan parasite of cattle, is essential in the management of disease control and in epidemiological studies. The currentlyused methods of diagnosis are blood smear examination and serological tests which include agglutination and immunofluorescence tests. These testes have been used the fild but because they lack sensitivity and specificity, never and improved methods of diagnosis are being developed. The quantitative buffy coat (OBC) method, using microhaematocrit tubes and acridine orange staining allows rapid and quicker diagnosis of B. bigemina and other blood parasites compared to light microscopic examination of stained smears. Parasite specific monoclonal antibodies have been used in antigen/antibody capture enzymelinked immunosorbent assays with grater sensitivity and specificity than previously described serological tests. Similary, DNA probes, derived from a repetitive sequence of the B. bigemina genome, offer a method of detecting very small numbers of parasites which are undetectable by conventional microscopy. An extrachromosomal DNA element, present in all the tick-borne protozoan parasites so far tested, provides an accurate means of diferentiating mixed parasite populations in infected animals. These improved methods will greatly facilitate epidemiological studies.