Once you have built up a time series, you will probably want to retrieve historical data.
构建一个时间系列后，您可能想要检索历史数据。
The embedded ts() function creates a time series object out of the vector glarp$livingroom.
嵌入的ts()函数通过向量glarp$livingroom创建一个时间序列对象。
RRDtool is an open source, high performance data logging and graphing system for time series data.
RRDtool是一个开放源码的高性能数据日志记录和绘图系统，用于处理时间系列数据。
So if your big data infrastructure must cope with time series, Informix is more than up to the job.
所以如果您的大数据基础架构必须处理时间序列，Informix已足够完成此工作。
Experiments have shown that this method can efficiently analyze the time series of Chinese Stock Market.
试验表明，用此方法分析中国证券市场的股票时间序列非常有效。
It discusses and compares the forecasting models using neural networks and using time series.
讨论、比较了基于神经网络和基于时间序列的预测模型。
The example result shows that the random-sets method is a nice approach to time series analysis.
实例结果分析表明，随机集模型是一种很好的时间序列分析方法。
The non-linear theory has been playing an important role in describing volatility of financial time series.
非线性理论在刻画金融时间序列的波动方面有着非常重要的作用。
Currently, the surrogate data method has become a widely used method in testing nonlinearity of time series.
目前，替代数据方法已逐渐成为时间序列的非线性成分检验中广为采用的一种方法。
Their similarity depends on the structure in the phase space of the time series of original observations fields.
它们的相似性依赖于原观测场时间序列在相空间中的结构。
This shows that the HEMA has great potential to provide a new and powerful tool for the analysis of time series.
这表明本算法的研究可为时间序列的分析提供一个崭新而有力的工具。
In order to study further this type of time series, it is necessary to extract deterministic and stochastic components.
为了进一步研究这种类型的时间系列，有必要提取确定性和随机成分。
Test of nonlinearity of time series is very important for nonlinear time series analysis and study of chaotic dynamics.
时间序列的非线性检测对于非线性时间序列分析、混沌特性研究有着重要意义。
The time series of temperature are expected to be the longest possible so as to examine various modes of oscillation periods.
人们希望温度的时间系列尽可能地长，以便能研究各种波的振荡周期。
Rough set theory, as an effective tool to deal with vagueness and uncertainty, is effective to the time series data mining.
粗糙集理论作为一种处理模糊和不确定性问题的有效工具，对时间序列的数据挖掘是有效的。
In the analysis of time series, the surrogate data test is often performed in order to investigate nonlinearity in the data.
替代数据检验法是检验时间序列中是否存在确定性非线性成分的重要统计方法。
The mining accuracy chart TAB cannot be used with time series models or with models that have continuous predictable attributes.
“挖掘准确性图表”选项卡不能用于时序模型或具有可预测连续属性的模型。
R provides still more tools for time series analysis. For example, we can plot the autocorrelation function for the living room temperature.
R还具有更多用于时间序列分析的工具。
The theory and method of modeling volatility persistence of time series is a powerful tool in analyzing the risk of economic and finance market.
时间序列的波动持续性建模理论和方法是经济金融领域风险分析的一种强有力的工具。
This hybrid model synthesizes the merits of multiple intelligent computation methods and offers a new effective solution of time series data mining.
该混合模型融合多种智能计算方法优点于一体，为时序数据挖掘提供了一种新的实用方法。
The course is the advanced part in a PhD econometrics sequence. It provides developments in theory and methods of nonlinear time series econometrics.
本课程是博士生计量经济学系列课程的高级内容，介绍非线性时间序列的理论和方法的前沿研究。
ARMA model is one of the most common models in the modern time series analysis which is widely used in scientific researches and engineering systems.
ARMA模型是现代时间序列分析中最为常用的模型之一，在科学研究和工程系统中具有广泛的运用。
The case study shows that the time series analysis method is an effective and practical one for groundwater resources evaluation and system management.
实例研究表明，应用时间序列分析法模拟地下水资源系统，进行地下水资源评价和系统管理简单、易行、省时、省力。
Therefore, how to describe the dynamic behavior of the financial time series' fluctuation well is always a hot research point in Financial Econometrics.
因此，如何有效地刻画金融时间序列波动的动态行为一直是金融计量学研究的热点问题。
The volatility is not only a universal phenomenon existing in the financial time series, but also a core research question to describing the financial market.
波动性不仅普遍存在于金融时间序列之中，而且也是金融市场研究中的一个核心问题。
Many economists keep on working hard, making a great effort to try to find a time series model which can capture most of these characteristics of financial data.
许多经济学家们不懈努力，孜孜以求，试图找到一个能够全面地刻划金融数据这些特性的时间序列模型。
I basically know the answer: temperature is a noisy time series, so if you pick and choose your dates over a short time span you can usually make whatever case you want.
我基本上知道答案，气温是一条嘈杂的时间序列，所以如果你在一下相对较短的时间跨度里挑选数据，你可以得到任何你想要的结果。
The CEIC China Premium Database is the recognized leader for China's economic data, with unrivalled breadth and depth of national, regional and industry time series.
CEIC中国数据库是业内领先的时间序列经济数据库，数据内容包括全国性的宏观经济数据、地区经济数据、行业经济数据及专题数据。
The CEIC China Premium Database is the recognized leader for China's economic data, with unrivalled breadth and depth of national, regional and industry time series.
CEIC中国数据库是业内领先的时间序列经济数据库，数据内容包括全国性的宏观经济数据、地区经济数据、行业经济数据及专题数据。
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