时间序列分析运用ARMA（q，p）模型，如何确定q、p的取值 如何利用matlab确定时间序列ARMA模型的阶数
\u8c01\u53ef\u4ee5\u5e2e\u5fd9\u63d0\u4f9b\u51e0\u7bc7\u5173\u4e8eARIMA\u9884\u6d4b\u95ee\u9898\u7684\u8bba\u6587!\u3000\u3000\u5229\u7528ARIMA\u6a21\u578b\u8fdb\u884c\u5377\u70df\u9500\u552e\u9884\u6d4b
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\u3000\u3000ARIMA\u6a21\u578b\u5229\u7528\u5927\u91cf\u7684\u5386\u53f2\u6570\u636e\u6765\u5efa\u6a21\uff0c\u7ecf\u8fc7\u6a21\u578b\u8bc6\u522b\u3001\u53c2\u6570\u4f30\u8ba1\u6765\u786e\u5b9a\u4e00\u4e2a\u80fd\u591f\u63cf\u8ff0\u6240\u7814\u7a76\u65f6\u95f4\u5e8f\u5217\u7684\u6570\u5b66\u6a21\u578b\uff0c\u6700\u540e\u518d\u7531\u8be5\u6a21\u578b\u63a8\u5bfc\u51fa\u9884\u6d4b\u6a21\u578b\uff0c\u8fdb\u800c\u8fbe\u5230\u9884\u62a5\u7684\u76ee\u7684\u3002ARMA\u6a21\u578b\u6709\u4e09\u79cd\u57fa\u672c\u5f62\u5f0f\uff1a\u81ea\u56de\u5f52\u6a21\u578b\uff08autoregressive\uff0cAR\uff09\u3001\u79fb\u52a8\u5e73\u5747\u6a21\u578b\uff08movingaverage\uff0cMA\uff09\u4ee5\u53ca\u81ea\u56de\u5f52\u79fb\u52a8\u5e73\u5747\u6a21\u578b\uff08\u6216\u6df7\u5408\u6a21\u578b\uff09\uff08auto-regressive Moving Average\uff0cARMA\uff09[3]\u3002
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\u3000\u3000\u5982\u679c\u65f6\u95f4\u5e8f\u5217{yt}\u6ee1\u8db3\uff1a
\u3000\u3000yt=\u03c61yt-1+\u2026+\u03c6pyt-p+\u03b5t\u4e86\uff081\uff09
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\u3000\u3000yt=\uff08\u03c61B+\u2026+\u03c6pBP\uff09yt+\u03b5t
\u3000\u3000\u4ee4\u03c6\uff08B\uff09=1-\u03c61B-\u2026-\u03c6pBP\uff0c\u5219\u6a21\u578b\uff081\uff09\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a
\u3000\u3000\u03c6\uff08B\uff09yt=\u03b5t
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\u3000\u3000\u5982\u679c\u65f6\u95f4\u5e8f\u5217{yt}\u6ee1\u8db3\uff1a
\u3000\u3000yt=\u03b5t\u2013\u03b81\u03b5t-1\u2013\u2026\u2013\u03b8qyt-q\uff082\uff09
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\u3000\u3000yt=\u03b8\uff08B\uff09\u03b5t
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\u3000\u3000\u5982\u679c\u65f6\u95f4\u5e8f\u5217{yt}\u6ee1\u8db3\uff1a
\u3000\u3000yt=\u03c61yt-1+\u2026+\u03c6pyt-p+\u03b5t-\u2013\u03b81\u03b5t-1\u2013\u2026\u2013\u03b8qyt-q
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\u3000\u3000\u03c6\uff08B\uff09yt=\u03b8\uff08B\uff09\u03b5t
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\u3000\u30003.\u8ba1\u7b97\u81ea\u76f8\u5173\u548c\u504f\u76f8\u5173\u7cfb\u6570\uff0c\u68c0\u9a8c\u9884\u5904\u7406\u540e\u7684\u6570\u636e\u662f\u5426\u7b26\u5408ARMA\u5efa\u6a21\u8981\u6c42\u3002
\u3000\u30004.ARIMA\u6a21\u578b\u7684\u8bc6\u522b\u3002\u6839\u636e\u81ea\u76f8\u5173\u7cfb\u6570\uff08AC\uff09\u53ca\u504f\u76f8\u5173\u7cfb\u6570\uff08PAC\uff09\u7684\u622a\u5c3e\u6027\uff0c\u521d\u6b65\u5224\u522b\u5e8f\u5217\u5c5e\u4e8e\u54ea\u7c7b\u6a21\u578b\u4ee5\u53ca\u6a21\u578b\u9636\u6b21\uff0c\u5e94\u7528AIC\u51c6\u5219\u4e3a\u6a21\u578b\u5b9a\u9636\u3002
\u3000\u30005.\u53c2\u6570\u4f30\u8ba1\u540e\uff0c\u5bf9ARIMA\u6a21\u578b\u7684\u9002\u5408\u6027\u8fdb\u884c\u68c0\u9a8c\uff0c\u5373\u5bf9\u6a21\u578b\u7684\u6b8b\u5dee\u5e8f\u5217\u8fdb\u884c\u767d\u566a\u58f0\u68c0\u9a8c\uff0c\u5982\u679c\u4e0d\u80fd\u901a\u8fc7\uff0c\u5219\u5fc5\u987b\u5bf9\u6a21\u578b\u91cd\u65b0\u8fdb\u884c\u5b9a\u9636\u3002
\u3000\u30006.\u7528ARIMA\u6a21\u578b\u9884\u6d4b\u6708\u5ea6\u5377\u70df\u9500\u552e\u91cf\uff0c\u4ee5\u6b64\u6570\u636e\u53ef\u4ee5\u6307\u5bfc\u70df\u8349\u516c\u53f8\u7684\u6708\u5ea6\u548c\u5b63\u5ea6\u5377\u70df\u7684\u9500\u552e\u3002
\u3000\u3000\u4e09.\u67d0\u70df\u8349\u516c\u53f8\u5377\u70df\u9500\u552e\u6a21\u578b\u5206\u6790
\u3000\u30001.\u6574\u7406\u6570\u636e\u3002
\u3000\u3000\u672c\u6587\u6240\u7528\u6570\u636e\u4e3a\u67d0\u70df\u8349\u516c\u53f8\u8fd1\u56db\u5e74\u591a\u7684\u5377\u70df\u9500\u552e\u91cf\uff0c\u5982\u88681\u6240\u793a\u3002
\u3000\u3000\u88681\u5377\u70df\u5386\u53f2\u9500\u552e\u6570\u636e
\u3000\u3000\u56fe1\u5377\u70df\u9500\u552e\u66f2\u7ebf\u56fe
\u3000\u3000\u7531\u56fe1\u53ef\u660e\u663e\u770b\u51fa\uff0c\u5377\u70df\u9500\u552e\u6570\u636e\u5177\u6709\u6574\u4f53\u5747\u52bf\u53d8\u52a8\u6027\u548c\u5b63\u8282\u6ce2\u52a8\u6027\uff0c\u5177\u5907\u65f6\u95f4\u5e8f\u5217\u4e8c\u91cd\u8d8b\u52bf\u53d8\u5316\u7279\u70b9\u3002
\u3000\u30002.\u6570\u636e\u5e8f\u5217\u5e73\u7a33\u5316
\u3000\u3000\u7531\u56fe1\u53ef\u770b\u51fa\u6570\u636e\u5e8f\u5217\u6709\u8d8b\u52bf\u6027\uff0c\u4e3a\u975e\u5e73\u7a33\u5e8f\u5217\uff0c\u9700\u5bf9\u5176\u8fdb\u884c\u5e73\u7a33\u5316\u5904\u7406\u3002\u5bf9\u6570\u636e\u8fdb\u884c\u4e00\u9636\u5dee\u5206\u540e\u7684\u5e8f\u5217\u56fe\u5982\u56fe2\u3002
\u3000\u3000\u56fe2\u4e00\u9636\u5dee\u5206\u540e\u7684\u5e8f\u5217\u56fe
\u3000\u3000\u56fe2\u53ef\u4ee5\u770b\u51fa\u5df2\u7ecf\u6d88\u9664\u4e86\u8d8b\u52bf\u6027\uff0c\u4f46\u4ecd\u5177\u6709\u5b63\u8282\u6027\uff0c\u505a\u5b63\u8282\u5dee\u5206\uff0c\u5982\u56fe3\u3002
\u3000\u3000\u56fe3\u3001\u5b63\u8282\u5dee\u5206\u540e\u7684\u5e8f\u5217\u56fe
\u3000\u30003.\u8ba1\u7b97\u81ea\u76f8\u5173\u548c\u504f\u76f8\u5173\u7cfb\u6570\uff0c\u68c0\u9a8c\u9884\u5904\u7406\u540e\u7684\u6570\u636e\u662f\u5426\u7b26\u5408ARMA\u5efa\u6a21\u7684\u8981\u6c42\u3002
\u3000\u3000\u4e00\u9636\u5dee\u5206\u3001\u5b63\u8282\u5dee\u5206\u540e\u7684\u5e8f\u5217\u7684\u76f8\u5173\u7cfb\u6570\u548c\u504f\u76f8\u5173\u7cfb\u6570\u5982\u56fe4\u6240\u793a\u3002
\u3000\u3000\u56fe4\u3001\u5b63\u8282\u5dee\u5206\u5e8f\u5217\u7684\u76f8\u5173\u7cfb\u6570\u548c\u504f\u76f8\u5173\u7cfb\u6570
\u3000\u3000\u7531\u4e0a\u56fe\u53ef\u4ee5\u770b\u5230\uff0c\u65f6\u95f4\u5e8f\u5217\u7684\u81ea\u76f8\u5173\u7cfb\u6570\u57fa\u672c\u4e0a\u90fd\u843d\u5165\u4e86\u7f6e\u4fe1\u533a\u95f4\uff0c\u4e14\u9010\u6e10\u8d8b\u4e8e\u96f6\u3002\u53ef\u4ee5\u5224\u65ad\u8be5\u65f6\u95f4\u5e8f\u5217\u5e73\u7a33\u3002
\u3000\u30004.ARMA\u6a21\u578b\u7684\u8bc6\u522b\u3001\u53c2\u6570\u4f30\u8ba1\u53ca\u68c0\u9a8c\uff1a
\u3000\u3000\u4ee5AIC\u539f\u5219\u5b9a\u9636\u3002AIC\u51c6\u5219\u79f0\u4e3a\u6700\u5c0f\u4fe1\u606f\u7684\u8fa8\u8bc6\u6a21\u578b\u9636\u6570\u51c6\u5219\u3002\u8be5\u51c6\u5219\u7684\u57fa\u672c\u601d\u60f3\u662f\uff0c\u6839\u636e\u6a21\u578b\u7684\u9884\u62a5\u8bef\u5dee\u6765\u5224\u65ad\u81ea\u56de\u5f52\u6a21\u578b\u7684\u9636\u6570\u662f\u5426\u5408\u9002\uff0c\u5982\u679c\u67d0\u4e2a\u9002\u7528\u7684\u81ea\u56de\u5f52\u6a21\u578b\u662f\u7531\u67d0\u4e00\u5e8f\u5217\u62df\u5408\u5f97\u6765\u7684\uff0c\u5219\u5229\u7528\u8be5\u6a21\u578b\u5bf9\u5e8f\u5217\u8fdb\u884c\u4e00\u6b65\u9884\u6d4b\uff0c\u6240\u5f97\u7684\u9884\u6d4b\u8bef\u5dee\u5fc5\u5b9a\u662f\u6700\u5c0f\u7684\u3002\u7531\u6b64\u5f97\u51fa\u6700\u4f18\u6a21\u578b\u4e3a\uff1aLog ARIMA\uff080\uff0c1\uff0c2\uff09\uff080\uff0c1\uff0c1\uff09s NOINT\u3002
\u3000\u3000\u6a21\u578bLog ARIMA\uff080\uff0c1\uff0c2\uff09\uff080\uff0c1\uff0c1\uff09s NOINT\u6b8b\u5dee\u9879\u7684ACF\u3001PACF\u3001IACF\u56fe\u5982\u4e0b\uff1a
\u3000\u3000\u56fe5\u6a21\u578bLog ARIMA\uff080\uff0c1\uff0c2\uff09\uff080\uff0c1\uff0c1\uff09s NOINT\u6b8b\u5dee\u9879\u7684ACF\u3001PACF\u3001IACF\u56fe
\u3000\u3000\u53c2\u6570\u4f30\u8ba1\u548c\u6a21\u578b\u62df\u5408\u540e\uff0c\u5e94\u5bf9 ARIMA\u6a21\u578b\u7684\u9002\u5408\u6027\u8fdb\u884c\u68c0\u9a8c \uff0c\u5373\u5bf9\u6a21\u578b\u7684\u6b8b\u5dee\u5e8f\u5217\u8fdb\u884c\u767d\u566a\u58f0\u68c0\u9a8c\u3002\u82e5\u6b8b\u5dee\u5e8f\u5217\u4e0d\u662f\u767d\u566a\u58f0\u5e8f\u5217 \uff0c\u610f\u5473\u7740\u6b8b\u5dee\u5e8f\u5217\u8fd8\u5b58\u5728\u6709\u7528\u4fe1\u606f\u6ca1\u88ab\u63d0\u53d6\uff0c\u9700\u8981\u5bf9\u6a21\u578b\u91cd\u65b0\u8fdb\u884c\u8bc6\u522b\u3002
\u3000\u3000\u56fe6\u6a21\u578bLog ARIMA\uff080\uff0c1\uff0c2\uff09\uff080\uff0c1\uff0c1\uff09s NOINT\u6b8b\u5dee\u9879\u7684\u767d\u566a\u58f0\u548c\u5355\u4f4d\u6839\u68c0\u9a8c\u56fe
\u3000\u3000\u4ece\u4e0a\u9762\u56fe\u4e2d\u53ef\u4ee5\u770b\u51fa\uff0c\u6a21\u578b\u6b8b\u5dee\u9879\u4e3a\u767d\u566a\u58f0\uff0c\u4fe1\u606f\u63d0\u53d6\u5145\u5206\u3002
\u3000\u3000\u6a21\u578b\u62df\u5408\u7edf\u8ba1\u91cf\u5982\u4e0b\uff1a
\u3000\u3000\u56fe7\u6a21\u578bLog ARIMA\uff080\uff0c1\uff0c2\uff09\uff080\uff0c1\uff0c1\uff09s NOINT\u62df\u5408\u7edf\u8ba1\u91cf
\u3000\u3000\u6a21\u578b\u7edf\u8ba1\u53c2\u6570\u5982\u4e0b\uff1a
\u3000\u3000\u56fe8\u6a21\u578bLog ARIMA\uff080\uff0c1\uff0c2\uff09\uff080\uff0c1\uff0c1\uff09s NOINT\u7edf\u8ba1\u53c2\u6570
\u3000\u30005.\u5229\u7528ARIMA\u6a21\u578b\u9884\u6d4b2009\u5e7411\u6708\u4efd-2010\u5e7412\u6708\u4efd\u7684\u9500\u552e\u6570\u636e
\u3000\u30002009\u5e7411\u6708\u4efd-2010\u5e7412\u6708\u4efd\u7684\u9500\u552e\u8d8b\u52bf\u9884\u6d4b\u56fe\u5982\u4e0b\uff1a
\u3000\u3000\u56fe9 2009\u5e7411\u6708\u4efd-2010\u5e7412\u6708\u4efd\u7684\u9500\u552e\u9884\u6d4b\u56fe
\u3000\u3000\u5bf92009\u5e7411\u6708\u4efd-2010\u5e7412\u6708\u4efd\u9500\u552e\u91cf\u7684\u9884\u6d4b\u53ca\u9884\u6d4b\u533a\u95f4\u5982\u4e0b\u8868\u3002
\u3000\u3000\u7efc\u4e0a\u6240\u8ff0\uff0c\u5229\u7528ARIMA\u6cd5\u5efa\u7acb\u5377\u70df\u9500\u552e\u9884\u6d4b\u6a21\u578b\u80fd\u591f\u8f83\u597d\u5730\u9884\u6d4b\u51fa\u89c4\u683c\u5377\u70df\u6708\u9500\u552e\u603b\u91cf\u503c\u53d8\u5316\u8d8b\u52bf\uff0c\u80fd\u591f\u5b9e\u73b0\u5bf9\u5377\u70df\u9500\u552e\u5b63\u8282\u6027\u3001\u5468\u671f\u6027\u548c\u968f\u673a\u6027\u7279\u70b9\u7684\u6709\u6548\u6a21\u62df\uff0c\u9884\u6d4b\u6570\u636e\u53ef\u4ee5\u4f5c\u4e3a\u5377\u70df\u6708\u5ea6\u548c\u5b63\u5ea6\u9500\u552e\u7684\u53c2\u8003\u3002
\u3000\u3000[\u53c2\u8003\u6587\u732e]
\u3000\u3000[1]\u7f57\u8273\u8f89\u3001\u5415\u6c38\u8d35\u3001\u674e\u5f6c\uff0c\u57fa\u4e8eARMA\u7684\u6df7\u5408\u5377\u70df\u9500\u552e\u9884\u6d4b\u6a21\u578b\uff0c\u8ba1\u7b97\u673a\u5e94\u7528\u7814\u7a76[J].2009.7
\u3000\u3000[2]\u962e\u656c\uff0cSAS\u7edf\u8ba1\u5206\u6790\u4ece\u5165\u95e8\u5230\u7cbe\u901a[M]\uff0c\u4eba\u6c11\u90ae\u7535\u51fa\u7248\u793e.2009
\u3000\u3000[3]\u5f90\u56fd\u5f3a\uff0c\u7edf\u8ba1\u9884\u6d4b\u548c\u51b3\u7b56[M]\uff0c\u4e0a\u6d77\u8d22\u7ecf\u5927\u5b66\u51fa\u7248\u793e.2008
\u6ee1\u610f\u8bf7\u91c7\u7eb3
%\u4e0b\u9762\u8981\u5bf9\u5dee\u5206\u4ee5\u540e\u7684\u5e8f\u5217\u8fdb\u884c\u62df\u5408\u548c\u9884\u6d4b\uff0c\u6c42\u51fa\u6700\u597d\u7684\u9636\u6570
z=[DX;zeros(12,1)];
z=iddata(z);
test=[];
for p=1:12
for q=1:12
m=armax(z(1:200),[p q]);
AIC=aic(m);
test=[test;p q AIC];
end
end
for k=1:size(test,1)
if test(k,3)==min(test(:,3))
p_test=test(k,1);
q_test=test(k,2);
break;
end
end
%\u62df\u5408
m1=armax(z(1:200),[p_test q_test]);
figure(5);
e = resid(m1,z);
plot(e);
set(gca,'Xlim',[0 ls]);
figure(6);
subplot(2,1,1)
autocorr(e.outputdata)
subplot(2,1,2)
parcorr(e.outputdata)
set(gca,'Xlim',[0 ls]);
%\u9884\u6d4b\u8fc7\u7a0b
pr=predict(m1,z,12);
po=pr.outputdata;
figure(7)
plot(po,'r')
hold on
plot(y,'b');
set(gca,'Xlim',[0 ls]);
另外根据Box-Jenkins建模方法，可以初步设定模型为ARMA（n，n-1），即自回归部分的阶数比滑动平均部分阶数高一阶，
不用eviews，如果用matlab，怎么确定呢？
绛旓細鍦ㄧ粺璁″鍜岀粡娴庡鐨勬鍫傞噷锛鏃堕棿搴忓垪鍒嗘瀽鏄竴闂ㄨ嚦鍏抽噸瑕佷笖瀵屾湁娣卞害鐨勯鍩熴ARMA妯″瀷锛鍏ㄧО鑷洖褰掔Щ鍔ㄥ钩鍧囨ā鍨嬶紙Auto-Regressive Moving-Average锛夛紝鍍忎竴搴фˉ姊侊紝灏嗚繃鍘讳笌鏈潵绱у瘑鐩歌繛銆傝鎴戜滑涓璧疯蛋杩汚RMA鐨勪笁澶ф牳蹇冪粍鎴愰儴鍒嗭細鑷洖褰掓ā鍨嬶紙AR锛夈佺Щ鍔ㄥ钩鍧囨ā鍨嬶紙MA锛夛紝浠ュ強瀹冧滑鐨勮瀺鍚堚斺擜RMA妯″瀷銆1. 鑷洖褰...
绛旓細鍦鏃堕棿搴忓垪鍒嗘瀽鐨勯鍩燂紝澶氱淮搴︾殑鏃堕棿搴忓垪浠ュ叾澶嶆潅鎬у紩浜哄叆鑳溿傛湰鏂囧皢娣卞叆鎺㈣澶氱淮骞崇ǔ搴忓垪鐨勬蹇碉紝浠ュ強鍏朵腑鐨勫叧閿ā鍨嬧斺ARMA妯″瀷锛鐗瑰埆鏄疺ARMA妯″瀷锛夊拰VAR(p)妯″瀷鐨勭壒鎬у拰浼拌鏂规硶銆備竴銆佸缁村钩绋冲簭鍒楃殑鍩虹煶褰搈涓椂闂村簭鍒楃粍鎴愮殑鍚戦噺 { }鍦ㄤ换鎰忓浐瀹氭椂闂磘涓嬬殑鍧囧煎拰鑷崗鏂瑰樊鍑芥暟涓庢椂闂磘鏃犲叧鏃讹紝鎴戜滑绉颁箣...
绛旓細1銆佸洜涓轰紶缁鏃堕棿搴忓垪鍒嗘瀽鎶鏈紙鏃堕棿搴忓垪鍒嗚В娉曪級鐨勭己闄凤紝鎵浠ョ粺璁″瀹跺紑鍙戝嚭鏇翠负閫氱敤鐨勬椂闂村簭鍒楀垎鏋愭柟娉曪紝鍏朵腑AR/MA/ARMA/ARIMA鍦ㄨ繖涓彂灞曡繃绋嬩腑鎵紨浜嗛潪甯搁噸瑕佺殑瑙掕壊锛岀洿鍒扮幇鍦紝瀹冧滑閮藉湪瀹為檯宸ヤ綔鐢熸椿涓彂鎸ラ噸瑕佷綔鐢ㄣ2銆佹椂闂村簭鍒楁槸鎸囦竴缁勫湪杩炵画鏃堕棿涓婃祴寰楃殑鏁版嵁锛屽叾鍦ㄦ暟瀛︿笂鐨勫畾涔夋槸涓缁勫悜閲弜(t)锛宼=...
绛旓細鏌ョ湅鑷浉鍏炽佸亸鐩稿叧绯绘暟鍥撅紝鑾峰彇鍏舵埅灏剧壒鐐癸紝浠庤岀‘瀹歱鍜宷 鍙﹀鏍规嵁Box-Jenkins寤烘ā鏂规硶锛屽彲浠ュ垵姝ヨ瀹氭ā鍨嬩负ARMA锛坣锛宯-1锛夛紝鍗宠嚜鍥炲綊閮ㄥ垎鐨勯樁鏁版瘮婊戝姩骞冲潎閮ㄥ垎闃舵暟楂樹竴闃讹紝
绛旓細瀵逛簬鏃堕棿搴忓垪鍒嗘瀽涓殑骞崇ǔ鏃堕棿搴忓垪锛孧A锛堢Щ鍔ㄥ钩鍧囷級鍜孉R锛堣嚜鍥炲綊锛夋ā鍨嬪彲浠ラ氳繃鏁板鍏紡杩涜浜掔浉杞寲锛岃ARMA锛鑷洖褰掔Щ鍔ㄥ钩鍧囷級妯″瀷鍒欏彲浠ョ敱AR鍜孧A妯″瀷缁勫悎寰楀埌銆傚叿浣撴潵璇达紝濡傛灉涓涓椂闂村簭鍒楁槸MA(q)妯″瀷锛屽垯瀹冨彲浠ヨ〃绀轰负涓涓櫧鍣０搴忓垪涓庢粸鍚庤宸」鐨勭嚎鎬х粍鍚堬紱濡傛灉杩欎釜鏃堕棿搴忓垪鏄疉R(p)妯″瀷锛屽垯瀹冨彲浠...
绛旓細鍒╃敤astsa鍖呯殑acf2()鍑芥暟鍙互鍚屾椂鐢诲嚭鏃堕棿搴忓垪鏁版嵁鐨凙CF鍥惧拰PACF鍥.涓嬮潰鐨勪緥瀛愬垎鍒敓鎴怉R(1),AR(2),MA(1)妯″瀷鐨勬暟鎹(鍒嗗埆瀵瑰簲x,y,z鏁版嵁)锛屽苟鏌ョ湅瀵瑰簲鐨凙CF鍥惧拰PACF鍥撅細鍗曠函鐨凙R鎴朚A妯″瀷鏍规嵁ACF鍜孭ACF鍥捐繕鏄瘮杈冨鏄撳畾闃剁殑锛屼絾p銆乹鍧囦笉涓0鐨ARMA妯″瀷瀹氶樁灏辨病杩欎箞绠鍗曚簡锛岃瑙佷笅涓涓瑪璁般
绛旓細涓や釜閮ㄥ垎鏄浉涔樼殑鍏崇郴銆傚洜姝わ紝ARIMA(p,d,q)(P,D,Q)涔熻绉颁负澶嶅悎瀛ｈ妭妯″瀷銆鏃堕棿搴忓垪鍒嗘瀽鐨勬枃绔犳洿鏂板埌杩欓噷锛屾诲叡浠嬬粛浜嗕袱涓椂闂村簭鍒楀垎鏋愮殑浣撶郴锛氭椂闂村簭鍒楀垎瑙ｆā鍨嬩綋绯诲拰AR/MA/ARMA/ARIMA妯″瀷浣撶郴銆備袱鑰呯殑鍒嗘瀽鍘熺悊鏄笉鍚岀殑锛屾椂闂村簭鍒楀垎瑙ｆ槸鍔涙眰灏嗘椂闂村簭鍒楀垎瑙ｆ垚涓嶅悓鐨勫彉鍔ㄦ垚鍒嗭紝鍒嗘瀽姣忕鍙樺姩鎴愬垎鐨勮寰嬶紝...
绛旓細鎻ず鏃堕棿搴忓垪鍒嗘瀽鐨勭瀵嗭細ARMA妯″瀷璇﹁В鍦ㄦ帰绱㈡暟鎹笘鐣屼腑锛孉RMA妯″瀷鐘瑰涓搴фˉ姊侊紝杩炴帴杩囧幓涓庢湭鏉ワ紝瀹冨叏绉颁负Auto-Regressive Moving Average (鑷洖褰掔Щ鍔ㄥ钩鍧)妯″瀷銆傝繖涓己澶х殑宸ュ叿鐢变袱涓牳蹇冪粍浠剁紪缁囪屾垚锛氶鍏堬紝AR(鑷洖褰)閮ㄥ垎锛屽鍚屽巻鍙茬殑鍥炲０锛屽埄鐢ㄨ繃寰鐨勮娴嬪兼彮绀哄綋鍓嶇殑鑴夊姩銆備互AR(1)涓轰緥锛屽畠鎻ず浜嗚繖鏍...
绛旓細鏃堕棿搴忓垪锛鍗虫暟鎹寜鏃堕棿椤哄簭鎺掑垪鐨勭壒娈婇殢鏈鸿繃绋嬶紝閫氳繃闈炶礋鏁存暟鏍囪涓嶅悓鐨勬椂鍒汇傚綋涓涓殢鏈鸿繃绋嬪彲浠ヨ〃鐜颁负鏃堕棿搴忓垪鏃讹紝鎴戜滑鑳藉杩愮敤鏃堕棿搴忓垪妯″瀷鏉ョ爺绌跺叾鐗规с鍒嗘瀽鏃堕棿搴忓垪閫氬父閬靛惊浠ヤ笅姝ラ锛氶鍏堬紝ARMA妯″瀷鏄父鐢ㄧ殑涓绉嶏紝鍏ㄧО鑷洖褰掔Щ鍔ㄥ钩鍧囨ā鍨嬨傚畠鍒嗕负AR锛堣嚜鍥炲綊锛夈MA锛绉诲姩骞冲潎锛夊拰ARMA涓変釜瀛愮被銆侫R妯″瀷...
绛旓細ARMA 妯″瀷锛Auto-Regressive and Moving Average Model锛夋槸鐮旂┒鏃堕棿搴忓垪鐨勯噸瑕佹柟娉曪紝鐢辫嚜鍥炲綊妯″瀷锛堢畝绉癆R妯″瀷锛変笌婊戝姩骞冲潎妯″瀷锛堢畝绉癕A妯″瀷锛変负鍩虹鈥滄贩鍚堚濇瀯鎴愩傚湪甯傚満鐮旂┒涓父鐢ㄤ簬闀挎湡杩借釜璧勬枡鐨勭爺绌讹紝濡傦細Panel鐮旂┒涓紝鐢ㄤ簬娑堣垂琛屼负妯″紡鍙樿縼鐮旂┒锛涘湪闆跺敭鐮旂┒涓紝鐢ㄤ簬鍏锋湁瀛ｈ妭鍙樺姩鐗瑰緛鐨勯攢鍞噺銆佸競鍦鸿妯＄殑...
