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261.
《Environmetrics》2018,29(2)
A key aspect of paleoclimate time series analysis is the identification of frequency behavior. Commonly, this is achieved by calculating a power spectrum and comparing this spectrum with that of a simplified model. Traditional hypothesis testing method can then be used to find statistically significant peaks that correspond to different frequencies. Complications occur when the data are multivariate or suffer from time uncertainty. In particular, the presence of joint uncertainties surrounding observations and their timing makes traditional hypothesis testing impractical. In this paper, we reexpress the frequency identification problem in the time domain as a variable selection model where each variable corresponds to a different frequency. We place this problem in a Bayesian framework that allows us to place shrinkage prior distributions on the weighting of each frequency, as well as include informative prior information through which we can take account of time uncertainty. We validate our approach with simulated data and illustrate it with analysis of mid‐ to late Holocene water table records from two sites in Northern Ireland—Dead Island and Slieveanorra. Both case studies also show the extent of the challenges that researchers may face. We therefore present one case that shows a good model fit with a clear frequency pattern and the other case where the identification of frequency behavior is impossible. We contrast our results with that of the extant methodology, known as REDFIT. 相似文献
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263.
兼性生化处理生活污水最佳工况研究 总被引：3，自引：0，他引：3
在常温条件下进行兼性生化处理生活污水试验,研究COD去除率与HRT、MLSS、进水有机物浓度和混合液水温的关系。在试验中最佳的水平搭配为MLSS=5500mg/L,进水有机物浓度=180mg/L,HRT=8h和混合液水温=20℃,与回归分析所得出MLSS=5881mg/L,进水有机物浓度=192.7mg/L,HRT=8.9063h和混合液水温=21.3790℃的最佳工艺条件相吻合。最后通过等高线分析得出常温下生活污水兼性生化的适宜范围。 相似文献
264.
被动扩散技术以其低成本、操作简单、空间覆盖率较高等优点已在西方国家广泛应用于环境空气质量监测与调查，辽宁省环保局通过欧盟项目引进，本技术在葫芦岛市环境空气质量监测应用有4年时间。依据4年环境空气被动扩散管监测基础数据，分析了解葫芦岛市城区大气中NO2时空分布特征：高浓度值出现在交通区，季节上呈现春季明显低于其它季节。 相似文献
265.
江西九岭地体南缘武功山地体北侧以及其间的萍乐盆地内，有大量的逆冲推覆构造分布。逆冲推覆构造的类型有两种──逆冲推覆型和重力滑覆型。逆冲推覆构造具有横向上对冲挤压，纵向上多层滑动的特征，据此笔者建立了一个可能的多层滑动──对冲挤压模式，并根据地质和同位素年龄资料讨论了逆冲推覆构造的演化历史，指出区内大规模逆冲推覆构造的形成时间为中生代晚期（119.6Ma）。 相似文献
266.
Kai Wang;Chuanwen Sun; 《Greenhouse Gases: Science and Technology》2024,14(3):456-469
For shallow buried mines, the cracks generated due to the mining activities will connect the surface ground and the working face through the gob, which may result in the gas exchange between the surface and underground. In this study, we proposed the gob gas flow model and verified its applicability based on the measured data on site in our previous research and discussed the effect of delay time of pressure variation between working face and surface ground on the airflow direction according to the simulation. The results suggest that the delay time of pressure variation is the main factor affecting the pressure difference between surface and working face and airflow direction. Due to the characteristics of the surface pressure changes, the effect of delay time on airflow in gob is small in a short time, but this effect gradually increases with time. According to the airflow law in a cycle of pressure variation, the airflow direction in the gob is predictable when the delay time reaches a certain value, which can be interpreted clearly on the surface pressure variation diagram. This research may provide references for the measures taken against mine disasters caused by different airflow directions. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd. 相似文献
267.
268.
In order to extract the time‐effect factors of multiple time series, a generalized time‐effect factor model (GTFM) and a statistic for identifying the model are proposed. This model is a general form of the Peña‐Box model. Based on the model, a pollen data set from Taiwan is analyzed. A factor, named temperature, is extracted. Its trend is then used to recover the weather of Taiwan over the past 5000 years. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
269.
270.
This article discusses dynamic factor analysis, a technique for estimating common trends in multivariate time series. Unlike more common time series techniques such as spectral analysis and ARIMA models, dynamic factor analysis can analyse short, non‐stationary time series containing missing values. Typically, the parameters in dynamic factor analysis are estimated by direct optimization, which means that only small data sets can be analysed if computing time is not to become prohibitively long and the chances of obtaining sub‐optimal estimates are to be avoided. This article shows how the parameters of dynamic factor analysis can be estimated using the EM algorithm, allowing larger data sets to be analysed. The technique is illustrated on a marine environmental data set. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献