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。
Parameter estimation is the key in building up a model in time series analysis.
时序模型的参数估计是时序模型建模的核心。
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。
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。
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。
ARIMA model; Predict; Time series analysis; Hypertension; Incidence.
ARIMA模型；预测；时间序列分析；高血压；发病率。
Finally, the random error model of HRG is established by using time series analysis method.
最后，采用时间序列分析方法建立了半球谐振陀螺的随机误差模型。
Furthermore, a random drift error model for IFOG is built by the method of time series analysis.
此外，采用时间序列分析方法，建立了IFOG的随机漂移误差模型。
The mid and long term forecast model based on the time series analysis has a good forecast effect.
建立在时间序列分析基础上的中长期预报模型具有很好的预报效果，可以用于作业预报。
Time series analysis techniques have been successfully used in the parameter identification of structures.
时间序列分析法已成功地用于结构的参数识别。
Comparing the linear regress analysis with the time series analysis, the latter's MAPE are less than the former.
将线性回归与时间序列分析进行比较，发现时序分析的平均绝对百分误差(MAPE)远远小于线性回归分析。
This paper deals with the adaptive signal deconvolution problem from the point of view of the time series analysis.
本文从时间序列分析观点处理自适应信号去卷问题。
This article discusses the main problem of time series analysis in the field of forecast application and programming.
本文讨论的主要问题是时间序列分析在预测领域的应用及编程实现。
Time series analysis and statistical test provide quantitative criteria to determine the optimum observation frequency.
时间序列分析和统计检验提供了优化地下水位监测频率的定量标准。
The prediction error correction is based on time series analysis, parameters estimation and optimum prediction principle.
预报误差校正是基于时间序列分析、参数估计和最优预报原理形成的。
Application of digital filtering and time series analysis to earthquake precursory processing is summarized in this paper.
本文概述了数字滤波和时间序列分析在地震前兆信息处理中的应用。
The obtained conclusion provides a premise for the application of chaotic time series analysis in well-log facies recognition.
这一结论为混沌时间序列分析方法应用于测井曲线识别领域提供了前提条件。
Time-series analysis sometimes errs but usually produces more accurate results when economists apply it to shorter time spans.
时间序列分析有时会出现错误，但是在更短的时间范围内能提供更准确的结果。
Time series analysis method is a main method by which deformation forecasting model is established in deformation measurements.
时间序列分析方法是建立变形测量预测模型的主要方法。
First, it introduces time series analysis principle. Then, heating load and model error prediction are given by this principle.
文中首先介绍了时间序列法预报原理，接着应用该原理给出供热负荷和模型误差的预报。
The time series analysis is proposed for load forecasting of power-generating and power transmission programming in power systems.
本文提出用于电力系统发电规划和输电规划负荷预测的时间序列分析法。
An algorithm of feature extraction and damage alarming based on auto-regressive moving-average (ARMA) time series analysis is presented.
本文基于时间序列分析ARMA模型探讨了结构损伤特征提取和损伤预警的实现方法。
The basic principle and method of time series analysis and its application in thermal error modeling on NC machine tools were presented.
提出了采用时间序列分析法进行机床热误差建模的基本原理及方法，及其在数控机床热误差补偿建模中的应用。
Time series analysis is an important method of the dynamic data analysis which has extensive researches and usages in many subject fields.
时间序列分析是动态数据分析的重要方法，在多学科领域中得到广泛的研究和运用。
The methods, which combine time series analysis and neural networks, are especially studied and applied in the model-unknown nonlinear system.
特别针对模型未知的非线性系统，研究了时间序列分析和神经网络相结合的故障预报方法。
As one of the branches of statistics, time series analysis focuses on the variation characters and trend of discrete ordered data series mainly.
时间序列分析是统计学的分支之一，它的研究对象是离散有序数列的变化特征和变化趋势。
The Support Vector Regression(SVR)is used for the time series analysis and prediction to resolve the complex nonlinear system modeling problems.
用支持向量回归（SVR）的方法分析和预测时间序列，可解决复杂非线性系统的建模问题。
In this paper, the theory and method of fuzzy time series analysis are presented, the model form and the parameters estimate problem are studied.
本文提出了模糊时间序列分析的理论和方法，研究了模型形式及其参数估计问题。
According to time series analysis principle, heating load with energy saving is predicted, which is taken as the set points for predictive control.
根据时间序列分析原理，对供热负荷进行节能预报并作为预测控制的设定值。
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。
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