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1.
H. Haario M. Laine M. Lehtinen E. Saksman J. Tamminen 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2004,66(3):591-607
Summary. We discuss the inversion of the gas profiles (ozone, NO3 , NO2 , aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion. 相似文献
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Impacts of complex emergencies or relief interventions have often been evaluated by absolute mortality compared to international standardized mortality rates. A better evaluation would be to compare with local baseline mortality of the affected populations. A projection of population-based survival data into time of emergency or intervention based on information from before the emergency may create a local baseline reference. We find a log-transformed Gaussian time series model where standard errors of the estimated rates are included in the variance to have the best forecasting capacity. However, if time-at-risk during the forecasted period is known then forecasting might be done using a Poisson time series model with overdispersion. Whatever, the standard error of the estimated rates must be included in the variance of the model either in an additive form in a Gaussian model or in a multiplicative form by overdispersion in a Poisson model. Data on which the forecasting is based must be modelled carefully concerning not only calendar-time trends but also periods with excessive frequency of events (epidemics) and seasonal variations to eliminate residual autocorrelation and to make a proper reference for comparison, reflecting changes over time during the emergency. Hence, when modelled properly it is possible to predict a reference to an emergency-affected population based on local conditions. We predicted childhood mortality during the war in Guinea-Bissau 1998-1999. We found an increased mortality in the first half-year of the war and a mortality corresponding to the expected one in the last half-year of the war. 相似文献
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范波 《重庆大学学报(社会科学版)》2002,8(5):33-35
文章介绍进入买方市场后 ,产能有限的制造企业进行需求管理的重要性 ,对需求管理的内涵、基本内容 (包括销售预测、订单管理、出货管理、销售分析 )、方法工具和工作流程进行具体分析。 相似文献
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组合预测误差信息矩阵研究 总被引:11,自引:0,他引:11
唐小我 《电子科技大学学报(社会科学版)》1992,(4)
研究组合预测误差信息矩阵的结构与组合预测方法性质之间的联系,首次提出冗余信息概念,对最优组合预测方法的组合结构进行了研究。 相似文献
6.
从MDnte Carlo模拟的实现过程入手,首先通过对Monte Carlo方法原理的阐述来介绍该种方法。进一步结合具体的实例通过计算机进行模拟来解释Monte Carlo方法的具体实现过程。重点讨论在选择合理的数据生成过程的前提下,如何在Monte Carlo方法中减少模拟方差,从而提高估计精度,更好地应用这种方法来进行经济预测。 相似文献
7.
Yen Steven T. Douglass Shaw W. Eiswerth Mark E. 《Review of Economics of the Household》2004,2(1):73-88
Asthma patients' health status may be especially sensitive to some types of air pollution, but the evidence on this is mixed. We explore the effects of ground-level ozone on asthma patient's activities, breaking apart the usual aggregated category of leisure into indoor and outdoor activities, and differentiating those by whether the activities were active or inactive. Applying the semiparametric censored estimation method we demonstrate that even though the period over which activities were observed was relatively low in ozone levels, there is a significant impact of ozone on a few activities. The (non-ozone) economic and demographic variables in the model play significant roles in explaining the allocation of time among seven activities, suggesting the suitability of the approach for other household decision-making contexts. 相似文献
8.
Traditionally, the autoregressive integrated moving average (ARIMA) model has been one of the most widely used linear models in time series forecasting. However, the ARIMA model cannot easily capture the nonlinear patterns. Support vector machines (SVMs), a novel neural network technique, have been successfully applied in solving nonlinear regression estimation problems. Therefore, this investigation proposes a hybrid methodology that exploits the unique strength of the ARIMA model and the SVMs model in forecasting stock prices problems. Real data sets of stock prices were used to examine the forecasting accuracy of the proposed model. The results of computational tests are very promising. 相似文献
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