x_arima.m

在matlab的环境下实现了自回归移动平均模型（arima）

%function [Yo_train,Yo_test,Yt_train,Yt_test,m,p_test,d_test,q_test] = x_arima(filename,test_num)
clear;
data=w_lodedata('aa.txt');
test_num=200;
n=size(data,1);
test = [];
ll = length(data);
%生成差分矩阵
dd=3;
matrix = zeros(ll,dd+1);
matrix(:,1) = data;

for i = 1:dd
    for j = i+1:ll
    matrix(j,i+1) = matrix(j,i) - matrix(j-1,i);
    end
end

% matrix(:,1)=data;
% n=size(data,1);
% for i=1:n-1
%     diff1(i)=data(i+1)-data(i);
% end 
% for i=1:n-2
%     diff2(i)=diff1(i+1)-diff1(i);
% end    
% for i=1:n-3
%     diff3(i)=diff2(i+1)-diff2(i);
% end
%         
% matrix(1,2)=0;
% matrix(2:n,2)=diff1;
% matrix(1:2,3)=0;
% matrix(3:n,3)=diff2;   
% matrix(1:3,4)=0;
% matrix(4:n,4)=diff3;

%d = [0 1 2 3];
%p = [0 1 2 3 4 5 6 7 8 9 10 11 12];
%q = [0 1 2 3 4 5 6 7 8 9 10 11 12];      

for d=0:dd
    x=matrix(:,d+1);
    v=x(d+1:end-test_num);
    u = iddata(v);
    for p = 0:12
        for q = 0:12
            m = armax(u,[p ])  
            AIC = aic(m)      
            test = [test;p q d AIC];
        end
    end
end 

%得出最优ARIMA模型的p，d，q参数
for k = 1:size(test,1)
    if test(k,4) == min(test(:,4)) 
       p_test = test(k,1);
       q_test = test(k,2);
       d_test = test(k,3);
    break;
    end
end

x=matrix(:,d_test+1);
v=x(d_test+1:end-test_num);
u = iddata(v);
%生成最优ARIMA模型
m = armax(u,[p_test q_test]) 
AIC = aic(m)  
disp(['  p_test',' ',p_test,])
disp(p_test)
disp(['  d_test',' ',d_test,])
disp(d_test)
disp(['  q_test',' ',q_test,])
disp(q_test)
predict_train = predict(m,u); 
Yt_arima_train=predict_train.OutputData;
    
 v=x(end-test_num+1:end);
 u = iddata(v);
 predict_test = predict(m,u); 
 Yt_arima_test=predict_test.OutputData;
 y=0;
    
 if d_test==0
    Yt_train=Yt_arima_train;
    Yt_test=Yt_arima_test;
 else 
    for i=1:(size(Yt_arima_train,1))
        for j=1:d_test
            y = matrix(i+d_test-1,j)+y;
        end
        Yt_train(i)=Yt_arima_train(i,1)+y;
        y=0;
    end
    Yt_train=Yt_train';
    for i=1:(size(Yt_arima_test,1))
        for j=1:d_test
            y = matrix(size(data,1)-test_num+i-1,j)+y;
        end
        Yt_test(i)=Yt_arima_test(i,1)+y;
        y=0;
    end
    Yt_test=Yt_test';
 end 
   
 
 Yo_train=data(d_test+1:end-test_num);
 Yo_test=data(end-test_num+1:end);

 %显示结果
  z_showresult(Yo_train,Yt_train, 'ARIMA train')
  z_showresult(Yo_test,Yt_test, 'ARIMA test')