869 resultados para estimating equations
Resumo:
A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.
Resumo:
There is concern that Pacific island economies dependent on remittances of migrants will endure foreign exchange shortages and declining Living standards as remittance levels drop due to lower migration rates and the belief that migrants' willingness to remit decreases over time. The empirical validity of the remittance-decay hypothesis has never been tested. From survey data on Tongan and Western Samoan migrants in Sydney, this paper estimates remittance functions using Tobit regression analysis. It is found that the remittance-decay hypothesis has no empirical validity and migrants are motivated by factors other than altruistic family support, including asset accumulation and investment back home. (C) 1997 Elsevier Science Ltd.
Resumo:
Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.
Resumo:
Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.
Resumo:
The suprathermal particles, electrons and protons, coming from the magnetosphere and precipitating into the high-latitude atmosphere are an energy source of the Earth's ionosphere. They interact with ambient thermal gas through inelastic and elastic collisions. The physical quantities perturbed by these precipitations, such as the heating rate, the electron production rate, or the emission intensities, can be provided in solving the kinetic stationary Boltzmann equation. This equation yields particle fluxes as a function of altitude, energy, and pitch angle. While this equation has been solved through different ways for the electron transport and fully tested, the proton transport is more complicated. Because of charge-changing reactions, the latter is a set of two-coupled transport equations that must be solved: one for protons and the other for H atoms. We present here a new approach that solves the multistream proton/hydrogen transport equations encompassing the collision angular redistributions and the magnetic mirroring effect. In order to validate our model we discuss the energy conservation and we compare with another model under the same inputs and with rocket observations. The influence of the angular redistributions is discussed in a forthcoming paper.
Resumo:
‘This book is a landmark opening and first attempt at such a process for defining farm forestry, as well as making a contribution to small-scale forestry.’
Resumo:
Objective: Several limitations of published bioelectrical impedance analysis (BIA) equations have been reported. The aims were to develop in a multiethnic, elderly population a new prediction equation and cross-validate it along with some published BIA equations for estimating fat-free mass using deuterium oxide dilution as the reference method. Design and setting: Cross-sectional study of elderly from five developing countries. Methods: Total body water (TBW) measured by deuterium dilution was used to determine fat-free mass (FFM) in 383 subjects. Anthropometric and BIA variables were also measured. Only 377 subjects were included for the analysis, randomly divided into development and cross-validation groups after stratified by gender. Stepwise model selection was used to generate the model and Bland Altman analysis was used to test agreement. Results: FFM = 2.95 - 3.89 (Gender) + 0.514 (Ht(2)/Z) + 0.090 (Waist) + 0.156 (Body weight). The model fit parameters were an R(2), total F-Ratio, and the SEE of 0.88, 314.3, and 3.3, respectively. None of the published BIA equations met the criteria for agreement. The new BIA equation underestimated FFM by just 0.3 kg in the cross-validation sample. The mean of the difference between FFM by TBW and the new BIA equation were not significantly different; 95% of the differences were between the limits of agreement of -6.3 to 6.9 kg of FFM. There was no significant association between the mean of the differences and their averages (r = 0.008 and p = 0.2). Conclusions: This new BIA equation offers a valid option compared with some of the current published BIA equations to estimate FFM in elderly subjects from five developing countries.
Resumo:
Prediction of carbohydrate fractions using equations from the Cornell Net Carbohydrate and Protein System (CNCPS) is a valuable tool to assess the nutritional value of forages. In this paper these carbohydrate fractions were predicted using data from three sunflower (Helianthus annuus L.) cultivars, fresh or as silage. The CNCPS equations for fractions B(2) and C include measurement of ash and protein-free neutral detergent fibre (NDF) as one of their components. However, NDF lacks pectin and other non-starch polysaccharides that are found in the cell wall (CW) matrix, so this work compared the use of a crude CW preparation instead of NDF in the CNCPS equations. There were no differences in the estimates of fractions B, and C when CW replaced NDF; however there were differences in fractions A and B2. Some of the CNCPS equations could be simplified when using CW instead of NDF Notably, lignin could be expressed as a proportion of DM, rather than on the basis of ash and protein-free NDF, when predicting CNCPS fraction C. The CNCPS fraction B(1) (starch + pectin) values were lower than pectin determined through wet chemistty. This finding, along with the results obtained by the substitution of CW for NDF in the CNCPS equations, suggests that pectin was not part of fraction B(1) but present in fraction A. We suggest that pectin and other non-starch polysaccharides that are dissolved by the neutral detergent solution be allocated to a specific fraction (B2) and that another fraction (B(3)) be adopted for the digestible cell wall carbohydrates.
Resumo:
A matricial method to solve the decay chain differential equations system is presented. The quantity of each nuclide in the chain at a time t may be evaluated by analytical expressions obtained in a simple way using recurrence relations. This method may be applied to problems of radioactive buildup and decay and can be easily implemented computationally. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
The true incidence of infectious diseases is difficult to determine from surveillance or from notification data. The proportion of new infections of rubella yields a model from serological surveys. The discrepancy between results and official notification data before vaccination era leads one to suspect the presence of hidden infections. Simulation on 80% of effective vaccination coverage shows a similar discrepancy of the total number of infections compared to notification data.
Inverse parabolicity of PDF equations in turbulent flows - reversed-time diffusion or something else