搜索资源列表
arima.rar
- 在matlab的环境下实现了自回归移动平均模型(arima),Matlab environment in the realization of the auto-regressive moving average model (arima)
Matlab-arima
- 金融时间序列分析,常用的一些模型分析过程,此仅对ARIMA 做了一些参考-Do time-series.look for some progrom refer to time series of Finalcial data,espeically using ARIMA model.
arima
- arima model to forecaste time series
hybrid-arima-nn-prediction-model
- hybrid arima-nn prediction model
arima
- 单变量时间序列的状态空间建模:电力消耗指数-Univariate ARIMA examples:An index of electricity consumption
ARIMA
- 是一个风速预测模型。适合初学者对ARIMA的理解(It is a wind speed prediction model. Suitable for beginners to understand ARIMA -------------------------------------------------------------------------------- --------------------------
ARIMA-GRNN hybrid model
- this code for ann analysis which very usefull for remote sensing and image processing you can free download arima texture code
ARIMA-master
- 实现时间序列的ARIMA模型的java实现方式(The Java class that implements the ARIMA model of time series)
ARIMA
- matlab-arima的具体编程,效果较好(matlab-arima Specific programming, the effect is better)
ARIMA
- arima算法实现思路,主要用来进行时间序列预测(The realization of ARIMA algorithm is mainly used for time series prediction)
ARIMA
- 应用pytho进行时间序列分析之arima(time analysis ARIMA using Python)
arima
- Matlab有关于ARIMA的源代码,内含几个M文件,包括估计、滤波、预报等。(It is the source code of arima by Matlab, which contains several M files, including estimation, filtering, prediction, etc.)
arima
- 通过一段ARIMA模型程序来预测股票上证指数(Prediction of Shanghai Stock Index by an ARIMA Model Program)
arima
- ARIMA基础代码,可根据已有的数据对数据可能走向进行预测预测。(ARIMA basic code, can achieve prediction.)
ARIMA
- ARIMA的实现,里面是matlab的代码,直接可以使用(ARIMA implementation, which contains matlab code, can be used directly)
arima预测(附Python和测试数据)
- 这是一个用python进行ARIMA预测的一个程序,希望能给各位带来帮助。(This is a python for ARIMA prediction of a program, I hope you can help.)
ARIMA数据集
- 这是关于ARIMA数据集,在进行arima预测时需要用到。(This is about the ARIMA data set, which is needed for ARIMA prediction.)
ARIMA预测
- ARIMA整合移动平均自回归模型,时间序列预测分析方法之一,可用于股价预测。(ARIMA integrates moving average autoregressive model and time series forecasting analysis method, which can be used for stock price forecasting.)
arima
- arima - (平稳性检验)根据时间序列的散点图、自相关系数和偏自相关系数、单位根检验(ADF),来判断数据的平稳性; - (平稳化处理)对非平稳的时间序列数据进行差分处理,得到差分阶数d; - (白噪声检测)为了验证序列中有用的信息是否已被提取完毕,如果为白噪声序列,(arima arima -(Stableness test) According to the time series of scatter plots, autocorrelation coefficients and
ARIMA
- ARIMA 模型是在平稳的时间序列基础上建立起来的,因此时间序列的平稳性是建模的重要前提。检验时间序列模型平稳的方法一般采用 ADF 单位根检验模型去检验。当然如果时间序列不稳定,也可以通过一些操作去使得时间序列稳定(比如取对数,差分),然后进行 ARIMA 模型预测,得到稳定的时间序列的预测结果,然后对预测结果进行之前使序列稳定的操作的逆操作(取指数,差分的逆操作),就可以得到原始数据的预测结果。(time series prediction ARIMA)