摘要
多项式趋势曲线是描述时间序列趋势性的一类非常重要的模型,被广泛应用在农业工业、环境能源等领域。本文从理论上采用局部求和方法给出了多项式模型参数的数学表达式,并借助时间序列分析理论分析模型残差是否为白噪声序列以建立相应的自回归滑动平均模型。在这些讨论的基础上,借助Matlab2013b和EViews8.0软件以白条猪价格指数为应用实例,详细地展示了多项式趋势模型参数的确定、模型的建立、模型的求解和误差分析等步骤。
The polynomial trend curve is a very important model to describe the trend of time series, which is widely used in agricultural and industry, environmental and energy, and other fields. In this paper, the mathematical expressions of polynomial model parameters are given by using local summation method, and the time series analysis theory is used to analyze whether the model residual errors are white noise series to establish the corresponding autoregressive moving average model. On the basis of these discussions and with the help of MATLAB 2013b software and EViews 8.0software, taking the Chinese pig price index as an example, the steps of determining the parameters of the polynomial trend model, establishing the model, solving the model and error analysis are all shown in details.
出处
《理论数学》
2019年第8期849-856,共8页
Pure Mathematics
基金
成都师范学院大学生创新创业训练计划项目(201814389100)。
