非平穩(wěn)時(shí)間序列分析.docx

此文檔收集于網(wǎng)絡(luò)，如有侵權(quán)請(qǐng)聯(lián)系網(wǎng)站刪除非平穩(wěn)時(shí)間序列分析1、 首先畫出時(shí)序圖如下：從時(shí)序圖中看出有明顯的遞增趨勢(shì)，而該序列是一直遞增，不隨季節(jié)波動(dòng)，所以認(rèn)為該序列不存在季節(jié)特征。故對(duì)原序列做一階差分，畫出一階差分后的時(shí)序圖如下：從中可以看到一階差分后序列仍然帶有明顯的增長(zhǎng)趨勢(shì)，再做二階差分：做完二階差分可以看到，數(shù)據(jù)的趨勢(shì)已經(jīng)消除，接下來(lái)對(duì)二階差分后的序列進(jìn)行檢驗(yàn)： AutocorrelationsLag Covariance Correlation -1 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 1 Std Error0 577.333 1.00000 | |*| 01 -209.345 -.36261 | *| . | 0.0712472 -52.915660 -.09166 | .*| . | 0.0800693 9.139195 0.01583 | . | . | 0.0806004 15.375892 0.02663 | . |* . | 0.0806155 -59.441547 -.10296 | .*| . | 0.0806606 -23.834489 -.04128 | . *| . | 0.0813247 100.285 0.17370 | . |* | 0.0814318 -146.329 -.25346 | *| . | 0.0832909 52.228658 0.09047 | . |*. | 0.08711810 21.008575 0.03639 | . |* . | 0.08759311 134.018 0.23213 | . |* | 0.08767012 -181.531 -.31443 | *| . | 0.09073613 23.268470 0.04030 | . |* . | 0.09610814 71.112195 0.12317 | . |* . | 0.09619415 -105.621 -.18295 | *| . | 0.09699116 37.591996 0.06511 | . |* . | 0.09872717 23.031506 0.03989 | . |* . | 0.09894518 45.654745 0.07908 | . |* . | 0.09902719 -101.320 -.17550 | *| . | 0.09934720 127.607 0.22103 | . |* | 0.10090821 -61.519663 -.10656 | . *| . | 0.10333722 35.825317 0.06205 | . |* . | 0.10389323 -93.627333 -.16217 | .*| . | 0.10408124 55.451208 0.09605 | . |* . |從其自相關(guān)圖中可以看出二階差分后的序列自相關(guān)系數(shù)很快衰減為零，且都在兩倍標(biāo)準(zhǔn)差范圍之內(nèi)，所以認(rèn)為平穩(wěn)，白噪聲檢驗(yàn)結(jié)果： Autocorrelation Check for White NoiseTo Chi- Pr Lag Square DF ChiSq -Autocorrelations-6 30.70 6 .0001 -0.363 -0.092 0.016 0.027 -0.103 -0.04112 84.54 12 .0001 0.174 -0.253 0.090 0.036 0.232 -0.31418 97.98 18 .0001 0.040 0.123 -0.183 0.065 0.040 0.07924 126.99 24 |t| LagMU 0.40286 0.16900 2.38 0.0181 0MA1,1 0.89063 0.03266 27.27 Lag Square DF ChiSq -Autocorrelations-6 24.69 6 0.0004 -0.138 0.189 0.022 0.061 0.011 0.05212 121.08 12 .0001 -0.082 0.043 -0.013 -0.128 0.068 -0.45418 128.87 18 .0001 0.041 -0.041 -0.081 -0.058 0.034 -0.06624 134.72 24 |t| LagMU 0.27979 5.67672 0.05 0.9607 0MA1,1 1.03722 0.02745 37.78 .0001 1MA1,2 -1.96578 0.02662 -73.86 .0001 2MA1,3 1.01221 0.02816 35.94 .0001 3MA1,4 -0.93338 0.02327 -40.11 .0001 4AR1,1 0.88707 0.05783 15.34 .0001 1AR1,2 -1.56109 0.07112 -21.95 .0001 2AR1,3 0.58435 0.09887 5.91 .0001 3AR1,4 -0.51306 0.07146 -7.18 |t| LagMA1,1 1.03708 0.02754 37.66 .0001 1MA1,2 -1.96564 0.02672 -73.57 .0001 2MA1,3 1.01208 0.02827 35.80 .0001 3MA1,4 -0.93333 0.02335 -39.97 .0001 4AR1,1 0.88696 0.05780 15.35 .0001 1AR1,2 -1.56094 0.07109 -21.96 .0001 2AR1,3 0.58434 0.09874 5.92 .0001 3AR1,4 -0.51307 0.07142 -7.18 .0001 4AR1,5 -0.11463 0.05462 -2.10 0.0365 5此時(shí)顯然參數(shù)檢驗(yàn)都顯著所以最終模型為：xt=1-0.88696B+1.56094B2-0.58434B3+0.51307B4+0.11463B5*t接下來(lái)利用此模型對(duì)未來(lái)一年6個(gè)月進(jìn)行預(yù)測(cè)：Forecasts for variable x時(shí)間 Forecast Std Error 95% Confidence Limits1982-1 3312.4933 107.6398 3101.5232 3523.46351982-2 3215.3428 145.0773 2930.9965 3499.68911982-3 3124.3113 187.5394 2756.7408 3491.88181982-4 2963.5109 221.5959 2529.1910 3397.83081982-5 3123.0553 254.8111 2623.6347 3622.47591982-6 3233.5793 284.3133 2676.3354 3790.8232預(yù)測(cè)圖為：本題代碼：data aa;input x;difx=dif(x);dif12x=dif12(difx);t=intnx(month,01jan1948d,_n_-1);format t year4.;cards;44665059256149159260463558051055355462870862972482086510071025955889965878110310929788238279288387207566588386847797547946816586446225887206707466166466785525605785145415765225305644425204845384544044244324585565066337081013103111011061104810059871006107585410087779828947957997817767618398428118437538487568488288578389868478017398657679418467687097988318337988067719517991156133212761373132513261314134312251133107510231266123711801046101010101046985971103710269471097101810549789551067113210921019111012621174139115331479141113701486145113091316131912331113136312451205108410481131113812711244113912051030130013191198114711401216120012711254120312721073137514001322121410961198113211931163112011649661154130611231033940115110131105101196310408381012963888840880939868100195696689684311801103104497289711031056105512871231107692911051127988903845102099410361050977956818103110619649678671058987111912021097994840108612381264117112061303139314631601149515611404170517391667159915161625162918091831166516591457170716071616152215851657171717891814169814811330164615961496138613021524154716321668142114751396170617151586147715001648174518562067185621042061280927832748264226282714269927762795267325582394278427512521237222022469268628152831266125902383267027712628238122242556251226902726249325442232249423152217210021162319249124322470219122412117237023922255207720472255223325392394234122312171248724492300238724742667279129042737284927232613295028252717259327032836293829753064309230632991;proc gplot;plot x*t difx*t dif12x*t;symbol c=black i=join v=star;run;proc arima;spot vt. 發(fā)現(xiàn)；認(rèn)出identify var=x(1);run;survey n. 調(diào)查；測(cè)驗(yàn)proc arima;innocent adj. 清白的；無(wú)罪的；天真的identify var=x(1,12) nlag=8 minic p=(0:5) q=(0:5);paperwork n. 文書工作estimate p=5 q=4 noint;forecast lead=6 id=t interval=month out=results;arrangement n. 安排；排列run;