Location:
Search - AR ARMA
Search list
Description: 基于matlab环境下的ARMA(1,1)模型的参数估计程序
Platform: |
Size: 797 |
Author: lucy |
Hits:
Description: 利用ARMA、AR、MA模型，以及周期图等进行系统参数估计-use ARMA, AR, MA model and cycle map for parameter estimation system
Platform: |
Size: 1024 |
Author: 家家 |
Hits:
Description: 用Cholesky分解求ARMA模型的参数并作谱估计。-Using Cholesky decomposition for ARMA model parameters and for spectral estimation.
Platform: |
Size: 3072 |
Author: 张华 |
Hits:
Description: 用Cholesky分解求ARMA模型的参数并作谱估计,这个程序是用C来实现的-Using Cholesky decomposition for ARMA model parameters and for spectral estimation, this procedure is achieved using C
Platform: |
Size: 2048 |
Author: dh |
Hits:
Description: 应用经典prony法和AR参数建模进行模态参数识别-Prony method and the application of the classical AR modeling parameters for modal parameter identification
Platform: |
Size: 1024 |
Author: ajax |
Hits:
Description: 用AR模型法进行功率谱估计的各种算法比较，包括自相关法，BURG法，ARMA模型估计，PISARENCO谐波分解法-AR model method used to carry out a variety of power spectrum estimation algorithms, including the auto-correlation method, BURG Act, ARMA model is estimated, PISARENCO harmonic decomposition method
Platform: |
Size: 3072 |
Author: 许全盛 |
Hits:
Description: ARMA模型时间序列分析法简称为时序分析法，是一种利用参数模型对有序随机振动响应数据进行处理，从而进行模态参数识别的方法。参数模型包括AR自回归模型、MA滑动平均模型和ARMA自回归滑动平均模型。这里给出了一个求出ARMA模型参数的MATLAB程序。-ARMA model for time series analysis method referred to as time series analysis is a parametric model for the orderly use of random vibration data in response to treatment, thereby to carry out modal parameter identification method. Parameter model including the autoregressive AR model, MA model and ARMA moving average Autoregressive Moving Average Model. Here gives an ARMA model parameters are obtained MATLAB procedures.
Platform: |
Size: 35840 |
Author: 宋知用 |
Hits:
Description: 基于matlab环境下的ARMA(1,1)模型的参数估计程序-Matlab environment based on ARMA (1,1) model parameter estimation procedures
Platform: |
Size: 1024 |
Author: lucy |
Hits:
Description: 《现代信号处理》中关于利用最小二乘法估计ARMA模型的参数，并进行谐波恢复的仿真程序-err
Platform: |
Size: 1024 |
Author: 史龙 |
Hits:
Description: ARMA谱估计-AR参数估计的总体最小二乘法-ARMA spectral estimation-AR parameter estimation of the overall least square method
Platform: |
Size: 1024 |
Author: 马士明 |
Hits:
Description: 一个用matlab实现的ARMA变换程序-a program of ARMA based on matlab
Platform: |
Size: 3072 |
Author: 王小军 |
Hits:
Description: Model Fitting using a Gui code in matlab. using AR,ARMA,MA models
Platform: |
Size: 4096 |
Author: mohammad |
Hits:
Description: 该程序是对在已知和未知参数的情况下用最小二乘法估计观测数据的ARMA模型的AR参数的仿真。-The program is known and the unknown parameters in the case of observational data with least square method to estimate the ARMA model of AR parameters of simulation.
Platform: |
Size: 1024 |
Author: tiana |
Hits:
Description: Exercise on kalman filter with model AR, ARMA, ecc.
Platform: |
Size: 49152 |
Author: chiara |
Hits:
Description: ARMA预测程序源代码，经二阶差分后对油价进行预测的实例。-a program to predict the price of oil， using ARMA module
Platform: |
Size: 4096 |
Author: Nicole |
Hits:
Description: 现代谱估计中，ar模型与arma模型的比较，性能的区别-Modern spectral estimation, ar arma model model and compare the difference between the performance
Platform: |
Size: 9216 |
Author: 崔焘 |
Hits:
Description: To estimate the parameters of ARMA(ip,iq) model and
estimate the PSD
First using the Cholesky decomposition method to solve eq(12.8.5)
to find AR model s parameters, this is finished by calling
subroutine MCHOLSK . Then call subroutine MARYUWA in twice to find
MA s parameters, this is done as same as subroutine MMAYUWA.-To estimate the parameters of ARMA(ip,iq) model and
estimate the PSD
First using the Cholesky decomposition method to solve eq(12.8.5)
to find AR model s parameters, this is finished by calling
subroutine MCHOLSK . Then call subroutine MARYUWA in twice to find
MA s parameters, this is done as same as subroutine MMAYUWA.
Platform: |
Size: 169984 |
Author: JYT |
Hits:
Description: ARMA 模型（Auto-Regressive and Moving Average Model）是研究时间序列的重要方法，由自回归模型（简称AR模型）与滑动平均模型（简称MA模型）为基础“混合”构成。在市场研究中常用于长期追踪资料的研究，如：Panel研究中，用于消费行为模式变迁研究；在零售研究中，用于具有季节变动特征的销售量、市场规模的预测等。(ARMA model is an important method for studying time series. It is composed of an autoregressive model (AR model) and a moving average model (MA model). In the market research is often used to study long-term tracking data such as: Panel, used to study the mode change in consumer behavior; retail research, for with the seasonal variation characteristics of the sales volume, market size forecast.)
Platform: |
Size: 120832 |
Author: 阿斯顿难题
|
Hits:
Description: ARMA 模型（Auto-Regressive and Moving Average Model）是研究时间序列的重要方法，由自回归模型（简称AR模型）与滑动平均模型（简称MA模型）为基础“混合”构成。在市场研究中常用于长期追踪资料的研究，如：Panel研究中，用于消费行为模式变迁研究；在零售研究中，用于具有季节变动特征的销售量、市场规模的预测等(ARMA model is an important method to study time series. It consists of auto regressive model (AR model) and moving average model (MA model). In the market research is often used to study long-term tracking data such as: Panel, used to study the mode change in consumer behavior; retail research, for with the seasonal variation characteristics of the sales volume, market size forecast)
Platform: |
Size: 1024 |
Author: dovemeng
|
Hits:
Description: ARIMA模型是通过将预测对象随时间推移而形成的数据序列当成一个随机序列，进而用一定的数学模型来近似表述该序列。根据原序列是否平稳以及回归中所包含部分的不同分为AR、MA、ARMA以及ARIMA过程。
在模型的使用过程中需要根据时间序列的自相关函数、偏自相关函数等对序列的平稳性进行判别；而对于非平稳序列一般都需要通过差分处理将其转换成平稳序列（ARIMA）；对得到的平稳序列进行建模以确定最佳模型（AR、MA、ARMA或者ARIMA）。在使用中最重要也是最关键的就是对序列进行参数估计，以检验其是否具有统计意义。(The ARIMA model uses a mathematical model to approximate the sequence of data by forming a sequence of data that is predicted over time. It is divided into AR, MA, ARMA and ARIMA processes according to the stability of the original sequence and the included part of the regression.
In the process of the model according to the autocorrelation function, the partial sequence of stationary sequence autocorrelation function of discrimination; and for non stationary sequences generally need treatment to convert it into stationary sequence by difference (ARIMA); for the stationary sequences obtained were modeled to determine the best model (AR ARMA, MA, or ARIMA). In use, the most important and most important is to estimate the parameters of the sequence to test whether it is statistically significant.)
Platform: |
Size: 2026496 |
Author: 艾玛菲尔
|
Hits: