搜索资源列表
AR_P_Choose_AIC
- ARMA模型用于时间序列预测模型中P的选择原则，AIC原则程序-choose of p for AR model
Wavelet
- 用Java编写的网络流量预测的源程序，其中用到了Mallat快速小波变换和自回归AR模型。-Jmichelle network traffic prediction of the source program, including the use of the Mallat fast wavelet transform and regression AR model.
containerforecast_stepwisefit
- 使用stepwise方法选择因变量的基于AR模型的时间序列预测程序-This alogrithm can select the predictors using step-wise policy and forecast the time series based on AR model.
MMSE
- 最小均方误差自适应格型块处理迭代算法 预测AR模型系数-Minimum mean square error iterative adaptive lattice block processing algorithm Predict the AR model coefficients
forecast
- AR模型预测算法，使用BIC准则定阶，简单易懂-AR model prediction, using the BIC criteria set order
Data-analysis-of-the-application
- 把时间序列分析的方法和理论引入业务监控中。本文的创新点 在于利用AR州人模型建模前，通过孤立点和变点检测对数据做预处理， 先用控制图法去除孤立点，然后用变点检测的方法定位变点，最后对变 点前后的时间序列分段预测，从而提高了预测的准确度和可信度 -Time series analysis methods and theoretical introduction of the service monitoring. Innovation of this paper is to use
felogit
- AR模型预测 MATLAB中常用的一些程序代码-AR model prediction in MATLAB to code
4643df097701
- arma 实现了数据从文件的输入，ar模型预测，arma模型预测，卡尔曼滤波器模型预测，利用图形用户界面编写-Realized the data from the file input, ar model predictions, arma model prediction, Kalman filter model predictions, using a graphical user interface for the preparation of-arma matlab实现了数据从文件的输入
RLS
- 本程序基于一阶AR模型，u(n)=-0.99u(n-1)+v(n)的线性预测。白噪声v(n)方差0.995.FIR滤波器的抽头数为2.遗忘因子0.98.用RLS算法实现u(n)的线性预测。并附有仿真图片-This procedure is based on a first-order AR model, u (n) =-0.99u (n-1)+v (n) of the linear prediction. White noise v (n) the number of taps of the t
LMS
- 基于一阶AR模型u(n)=0.99u(n-1)+v(n),白噪声方差0.93627.步长0.05.分别使用M=2和M=3抽头的滤波器，用LMS算法实现u(n)的线性预测估计。并附仿真图已被参考。-Based on a first-order AR model u (n) = 0.99u (n-1) the+v (n), the white noise variance 0.93627 step 0.05. Respectively with M = 2 and M = 3-tap filter,
rls_AR_pred
- 使用基本的递归最小二乘算法来预测实值AR过程信号-use basic RLS algorithm to predict real-valued AR process
lms_AR_pred
- 使用多维最小均方算法来预测AR过程的信号-use multidimensional LMS algorithm to predict AR process
AR_color
- 利用yuler-walker方法预测AR参数，其中第二部用到了一维线性扫描确定参数。-The yuler-walker method to predict the AR parameters, the second part of which used a one-dimensional linear scan to determine the parameters.
8289671mr
- AR模型，主要用于时间序列的建模和预测。能够解决平稳时间序列问题-AR model ,which is quite popular in sovling time series
AF
- AR模型预测，matlab环境下用AR谱估计算法实现AR模型谱估计-AR model prediction, matlab environment AR spectral estimation algorithm AR model spectrum estimation
AR_example
- 时间预测模型AR，AR模型的算法，对数据进行预测。-Time prediction model AR, AR model algorithm, the data to predict.
EMDthenAR
- 对数据先进行经验模态分解得到不同特征尺度的信号分量，然后对所有的信号分量用AR模型进行预测得到预测后的分量，然后将预测后的分量进行重构得到最终的预测信号。-The data first empirical mode decomposition characteristics of the signal components of different scales, and then for all signal components obtained by AR model to predict
ARmodel
- 生成一个正弦信号，使用levinson-durbin算法和最终预测阶数准则FPE估计其AR模型的阶数，并且通过解Yule-Walker方程求得AR模型的参数，进而求得该正弦信号的功率谱-Generating a sinusoidal signal, using levinson-durbin algorithm to predict the order and final order of the criteria FPE estimates its AR model and AR model
ARprediction
- 对序列建立AR模型，并以概率形式给出预测数列表达。先进行平稳性检验后求取自相关函数，用Y-W法求取模型参数，并应用FPE准则确定阶数，进行预测后，给出概率表达。-AR model for the sequence established, and the probability forecast given in the form of a list. After a smooth first autocorrelation function test strike strike model p
AR_with_remove
- 时间序列分析，AR模型，用于流数据预测与滤波 输入参数：y为原始数据矩阵，p为AR模型的阶数，la为自回归模型的遗忘系数 输出参数：预测值，置信区间，离群点等-Time series analysis, AR model for prediction and filtering data stream input parameters: y original data matrix, p is the order of the AR model, la self-forgetting c