时序预测 | MATLAB实现ARMA自回归移动平均模型时间序列预测

预测效果

基本介绍

MATLAB实现ARMA时间序列预测（完整源码和数据）
本程序基于MATLAB的armax函数实现arma时间序列预测；
实现了模型趋势分析、序列平稳化、AIC准则模型参数识别与定阶、预测结果与误差分析过程，逻辑清晰。
数据为144个月的数据集，周期为一年，最终实现历史数据的预测和未来两年数据的预报！
基于自回归移动平均模型时间序列预测.
评价指标包括:MAE、RMSE和MAPE等，代码质量极高，方便学习和替换数据。要求2018版本及以上。

程序设计

• 完整程序和数据下载方式：MATLAB实现ARMA时间序列预测。

%%  参数设置
model_arima = arima(p_arima, d_arima, q_arima);
fit_arima = estimate(model_arima, trainData);
forecast_arima = forecast(fit_arima, numel(testData));
%-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
% 计算模型拟合优度
fit_ar_test = 1 - sum((testData - forecast_ar).^2) / sum((testData - mean(testData)).^2);
fit_arma_test = 1 - sum((testData - forecast_arma).^2) / sum((testData - mean(testData)).^2);
fit_arima_test = 1 - sum((testData - forecast_arima).^2) / sum((testData - mean(testData)).^2);
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原文链接：https://blog.csdn.net/kjm13182345320/article/details/132632834
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[S,Q] = size(T);
% Randomly Generate the Input Weight Matrix
IW = rand(N,R) * 2 - 1;
% Randomly Generate the Bias Matrix
B = rand(N,1);
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
BiasMatrix = repmat(B,1,Q);
% Calculate the Layer Output Matrix H
tempH = IW * P + BiasMatrix;
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
switch TF
    case 'sig'
        H = 1 ./ (1 + exp(-tempH));
    case 'sin'
        H = sin(tempH);
    case 'hardlim'
        H = hardlim(tempH);
end
% Calculate the Output Weight Matrix
LW = pinv(H') * T';
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

参考资料

[1] https://blog.csdn.net/article/details/126072792?spm=1001.2014.3001.5502
[2] https://blog.csdn.net/article/details/126044265?spm=1001.2014.3001.5502