搜索资源列表
Timeprediction-AR-MATLAB
- 时间序列AR模型预测的matlab源文件，可直接运行，有仿真结果。-Time series prediction of the AR model matlab source file, can be directly operation, the simulation results.
AR
- matlab写的用于时间序列预测的AR模型的程序，对于线性的时间序列效果还是可以的。-Matlab written procedures for time series forecasting AR model, the linear effect of time-series.
t1
- 运用matlab编程计算时间序列中的ARMA（p,q）模型-Use of matlab programming to calculate the time series ARMA (p, q) model
write_tsbnd
- 自动提取时间序列水位，用于模型边界条件设置。-Automatic extraction of time series water level for the set of model boundary conditions.
prediction-by-wavelet-and-ARMA
- 采用小波和ARMA模型对时间序列进行预测-Wavelet and the ARMA model to forecast the time series
Matlab-algorithm-source-code-package
- 1.MatLab从入门到精通的源代码（1.13M） 2.matlab经典算法的程序（2.9M） 3.MATLAB精彩编程100例源码（3.8M) 4.概率分布函数（7个文件） 5.解决积分问题的matlab源程序 （6个文件） 6.时间序列分析的一些模型Matlab源码（自回归例题及M文件）-1.MatLab from entry to the proficient source code (1.13M) 2.matlab classical algorithm proced
8
- 基于模型的时间序列数据挖掘---聚类和预测相关问题研究 ---- Clustering and forecasting issues related to model-based time-series data mining
chapter
- 神经网络模型，chapter.m，对于预测时间序列有较好的稳定-Neural network model, chapter.m forecast time series has a better stability
AR
- 改进的AR时间序列分析模型，加入了窗口的概念，源码里有实例-Improved AR time series analysis model, adding the concept of the window, there are instances where the source
do_GARCH2
- Calculates various ARMA-GARCH models for a specified returns time series. Output: model matrix with tests on model residuals and AIC BIC criteria
garchuv
- RATS 时间序列GARCH,EGARCH,IGARCH,GARCH-M模型-time series GARCH model
multiScale_KalmanFilter
- 用多尺度卡尔曼滤波法，对信号参数进行识别估计。高频信号和低频信号识别结合起来改进了算法识别的精确度和准确度。-It is an implementation of hierarchical (a.k.a. multi-scale) Kalman filter using belief propagation. The model parameters are estimated by expectation maximization (EM) algorithm. In this impleme
arma
- 随机产生一个时间序列，基于C语言的基础上建立ARMA模型，进行拟合和预测-Randomly generate a time series, based on the ARMA model is based on the C language, fitting and forecasting
AR
- 实用的matlab时间序列ar模型，可以参考学习-Practical matlab time series ar model, can refer to learning
hmm-tutorial
- The Hidden Markov Model (HMM) is a popular statistical tool for modelling a wide range of time series data. In the context of natural language processing(NLP), HMMs have been applied with great success to problems such as part-of-speech tagging a
AMMA2MA
- 勇士时间序列分析中，将ARMA模型参数转化为等价的MA模型参数-The Warriors time series analysis, ARMA model parameter is converted to an equivalent MA model parameters
fractal-predict-pdf
- 该文章从混沌和分形的关系出发，基于奇异吸引子的分形结构和时间序列的自仿射特性，提出了一种混沌时间序列的预测方法。采用迭代函数系统跟踪混沌的局部运动轨迹，由此确定统计意义上放射性能最优的时间序列段，并分局吸引子定力和拼贴定理建立预测模型。-This article from the chaos and fractal relationship starting, based on the characteristics of self-affine fractal structure and ti
vol
- matlab金融时间序列ARMA建模 结果分析： 1.预测结果从第四步开始，预测值不再改变，因为ARMA是收敛的回归模型，而我们做的工作并不是模拟，所以，当预测步长足够长时，它最终将收敛于一个不变得预测值 2.既然预测值一样，为什么还原为成交量后，在置信区间下预测的最大值与预测均值的差比预测均值与最小值的差要大？因为将对数差分值还原时，需用到的指数函数为凹函数-matlab Financial Time Series the the ARMA modeling results Ana
markovchainmodel
- Markov Chain model for regime switching time series
bayes_bati
- 采用bayes方法进行模型的校正，先验分布和似然函数采用时间序列模型，压箱底的东西-Using Bayes method for the calibration of the model, the prior distribution and the likelihood function using time series models, bottom pressure thing