應(yīng)用回歸分析結(jié)課論文

應(yīng)用回歸分析結(jié)課論文》影響財(cái)政收入的相關(guān)因素的分析班級(jí)姓名學(xué)號(hào)：目錄TOC\o"1-5"\h\z問(wèn)題的提出4數(shù)據(jù)來(lái)源4回歸分析的模型方法介紹和總結(jié)5多元線(xiàn)性回歸模型53.1.1多元線(xiàn)性回歸模型的一般形式53.1.2多元線(xiàn)性回歸模型的基本假定6多元線(xiàn)性回歸參數(shù)的最小二乘估計(jì)74.SAS程序及結(jié)果輸出84.1.建立數(shù)據(jù)集，進(jìn)行相關(guān)分析84.2?將數(shù)據(jù)做標(biāo)準(zhǔn)化處理，建立回歸方程10異方差檢驗(yàn)114.4自相關(guān)檢驗(yàn)134.5.多重共線(xiàn)性檢驗(yàn)13方差擴(kuò)大因子法13特征根判定法144.6消除多重共線(xiàn)性154.6.1后退法154.6.2.逐步回歸194.7最佳子集回歸214.8嶺回歸224.9主成分回歸254.10偏最小二乘回歸255.結(jié)論26參考文獻(xiàn)28摘要本文選1985-2003年的農(nóng)業(yè)增加值，工業(yè)增加值，建筑業(yè)增加值，社會(huì)消費(fèi)總額，人口數(shù)，受災(zāi)面積六個(gè)因素通過(guò)多元線(xiàn)性回歸分析和嶺回歸對(duì)國(guó)家財(cái)政收入行分析，主要分析分析影響財(cái)政收入的主要原因，并聯(lián)系實(shí)際進(jìn)行分析，以供參考。關(guān)鍵詞：財(cái)政收入多元線(xiàn)性回歸多重共線(xiàn)性嶺回歸1?問(wèn)題的提出財(cái)政參與分配社會(huì)產(chǎn)品，在一國(guó)經(jīng)濟(jì)發(fā)展和分配體系中占有重要地位和作用?？梢杂辛Φ卮龠M(jìn)經(jīng)濟(jì)的發(fā)展促進(jìn)科學(xué)、教育、文化、衛(wèi)生事業(yè)的發(fā)展，促進(jìn)人民生活水平的提高，為鞏固國(guó)防提供可靠的物質(zhì)保障。且可調(diào)節(jié)資源配置，促進(jìn)社會(huì)公平，改善人民生活。促進(jìn)經(jīng)濟(jì)機(jī)構(gòu)的優(yōu)化和經(jīng)濟(jì)發(fā)展方式的轉(zhuǎn)變。在我國(guó)，財(cái)政收入的主體是稅收收入，因此在稅收體制及政策不變的條件下，財(cái)政收入會(huì)隨著經(jīng)濟(jì)繁榮而增加，隨著經(jīng)濟(jì)衰退而下降。本文利用回歸分析，確定影響我國(guó)財(cái)政收入主要因素。2?數(shù)據(jù)來(lái)源在研究國(guó)家收入時(shí)，我們把財(cái)政收入按形式分為：各項(xiàng)稅收收入，企業(yè)收入，債務(wù)收入，國(guó)家能源交通重點(diǎn)建設(shè)基金收入，基本建設(shè)貸款歸還收入，國(guó)家調(diào)節(jié)基金收入，其他收入等。為了建立國(guó)家財(cái)政收入回歸模型，我們以財(cái)政收入y（億元）為因變量，自變量如下：x1為農(nóng)業(yè)增加值（億元）；x2為工業(yè)增加值（億元）；x3為建筑業(yè)增加值（億元）；x4為人口數(shù)（萬(wàn)人）；X5為社會(huì)消費(fèi)總額（億元）；x6為受災(zāi)面積（萬(wàn)公頃）。根據(jù)中國(guó)統(tǒng)計(jì)年鑒，得到1985-2003年數(shù)據(jù)，如圖：年悄叫正；山以.丄業(yè)増加值建慌業(yè)曾力口直人□數(shù)社二消賽總前殳應(yīng)面枳19S5823619.59716&75.11058.513S0L.4443.6519S62122.01401311194aos.071?75.u74374471.419S72199.354075.713813^54.o5lu^35115420.91?SS2357.245So5.3LS2251131.&□1110.26□53i.□lS.719S92664.9□534.7Z20iT1282.981127.047u7i.2469.91丄2?37.-7602.11345.011143.33725?.33S4.74121勺護(hù)一4RR1ry1rf>4.s；s11HR.腫R工斗匚7nn.77.1久斗fS"cinR4.72174.4斗1171."1□"4-RH15.""1q*4S；+R.qn1nqqn.n斗R4n?n11RH.-.711斗RF.加124r.1n?nn.nmi?i'i4fns."211^R.n1ri2n+.7nnr.斗只1gn巧砂斗寸*一yn1?fi7.4Smi加F14F一RR17斗17.g22SH".?粘FiGFiR；.R2.1?11.2124774.1斗HF.211^97RCn1.14加柿一411E柿917X\.4R1223.897.77.^.94Ci9.R919亦9875.9524542.9119C4E10061.991?7C,.272915E.5521.551999114+4.加24519.11?C.11-111Fi7.F；Ci1価一加2324915.885S73.71Ci1￡84.53麗41Fi?.Ci471.1920011苛仇042G179.Ci9548.981nrc.1.Fir.1247一G1r；7n9n.2501.4520021祁石一Ci427390.811r)7Ci.n18527.181?H7.flCi42027.1499.m217in.29691.814771.?加「砧一1莎一腫45B42Fi4F.OCi3.回歸分析的模型方法介紹和總結(jié)多元線(xiàn)性回歸模型3.1.1多元線(xiàn)性回歸模型的一般形式設(shè)隨機(jī)變量y與一般變量x，x，…，x的線(xiàn)性回歸模型為：12pTOC\o"1-5"\h\zy=x+Px+?…+Px+￡(3.1)01122pp式中，P,P，…，P是p+1個(gè)未知參數(shù)，P稱(chēng)為回歸常數(shù)，P，…，P稱(chēng)為回歸01p01p系數(shù)。y稱(chēng)為被解釋變量(因變量)，x,x…,x是p個(gè)可以精確測(cè)量并控制的一般變量。12,p稱(chēng)為解釋變量(自變量)。p二1時(shí)，式(3.1)為一元線(xiàn)性回歸模型；p>2時(shí)，我們就稱(chēng)式(3.1)為多元線(xiàn)性回歸模型。￡是隨機(jī)誤差，與一元線(xiàn)性回歸一樣，對(duì)隨機(jī)誤差項(xiàng)我們常假定3.2)3.3)E(￡)=03.2)3.3)var(￡)=◎2稱(chēng)E(y)=P+Px+Px+?…+Px01122pp為理論回歸方程。對(duì)一個(gè)實(shí)際問(wèn)題，如果我們獲得n組觀(guān)測(cè)數(shù)(x,x,…,x;yX二1,2,…,n),則線(xiàn)性i1i2ipi回歸模型式(3.1)可表示為：ny=P+Px+Px+ny=P+Px+Px+…+P10111212py=P+Px+Px+…+P120121222y=P+Px+Px+…??+P01n12n2x+￡1p1x+￡2p2x+￡pnpn3.4)3.5)寫(xiě)成矩陣形式為：3.5)y=XP+8X是一個(gè)nx（p+1）階矩陣，稱(chēng)為回歸設(shè)計(jì)矩陣或資料矩陣。在實(shí)驗(yàn)設(shè)計(jì)中，X的元素是預(yù)先設(shè)定并可以控制的，人的主觀(guān)因素可作用其中，因而稱(chēng)X為設(shè)計(jì)矩陣。3.1.2多元線(xiàn)性回歸模型的基本假定為了方便地進(jìn)行模型的參數(shù)估計(jì)，對(duì)回歸方程式（3.4）有如下一些基本假定（1）解釋變量x，x,…，x是確定性變量，不是隨機(jī)變量，且要求12prank（X）=p+1<n。這里的rankG）=p+1<n，表明設(shè)計(jì)矩陣X中的自變量列之間不相關(guān)，樣本量的個(gè)數(shù)應(yīng)大于解釋變量的個(gè)數(shù)，X是一滿(mǎn)秩矩陣。（2）隨機(jī)誤差性具有零均值和等方差，即IeG）=02

rb2，i=JcovC,8）=*i,J=1,2,…,nij丄0，i豐j這個(gè)假定通常稱(chēng)為高斯一馬爾柯夫條件。eG）=0，即假設(shè)觀(guān)測(cè)值沒(méi)有系統(tǒng)誤差，隨i機(jī)誤差項(xiàng)8的平均值為零，隨機(jī)誤差項(xiàng)8的協(xié)方差為零，表明隨機(jī)誤差項(xiàng)在不同的樣本ii點(diǎn)之間是不相關(guān)的（在正態(tài)假定下即為獨(dú)立的），不存在序列相關(guān)，并且有相同的精度（3）正態(tài)分布的假定條件為：2)2)對(duì)于多元線(xiàn)性回歸的矩陣模型式（3.5），這個(gè)條件便可表示為8?NCq21）n由上述假定和多元正態(tài)分布的性質(zhì)可知，隨機(jī)變量y服從n維正態(tài)分布，回歸模型式（3.5）的期望向量E（y）=X0var(y)=b21n因此3.2.多元線(xiàn)性回歸參數(shù)的最小二乘估計(jì)多元線(xiàn)性回歸模型未知參數(shù)P，P，…，P，的估計(jì)與一元線(xiàn)性回歸方程的參數(shù)估計(jì)原理01p一樣，仍可采用最小二乘估計(jì)。對(duì)于y二鄧+8,所謂最小二乘法，就是尋找參數(shù)Po，P，…，P的估計(jì)值，使離差平方和Q（P，P，…，P）極小，即:1po1p00最小二乘估計(jì)要尋找?guī)譳Hr瓦使得（幾min（7；~fi）~陀込一^2Xi2min（7；~fi）~陀込一^2Xi2dQdQ2g（兒--A-爐;;；F.jJ-0ocfft*-j經(jīng)整理后得用矩陣形式表示的正規(guī)方程組XUy—X0=0移項(xiàng)得丘祁=衛(wèi)y當(dāng)卩勾存在時(shí)，即得回歸參數(shù)的量小二乘估計(jì)丸R=（X'X）_1K74.SAS程序及結(jié)果輸出■建立數(shù)據(jù)集，進(jìn)行相關(guān)分析程序1dataa;inputyearyx1-x6@@;cards;19852004.823619.59716675.11058.513801.4443.6519862122.01401311194808.071075.074374471.419872199.354675.713813954.6510935115420.919882357.245865.3182251131.651110.266534.6508.719892664.96534.7220171282.981127.047074.2469.9119902937.17662.1239241345.011143.337250.3384.7419913149.488157266251564.331158.238245.7554.729704.8513.3312462.1488.293483.379084.7345999704.8513.3312462.1488.294348.9510995.5484023253.51185.171198.516264.7550.431267.43206201198.516264.7550.431267.4320620546.886242.220340.9918945793.75200321715.2529691.814771.2200321715.2529691.814771.223083.871292.2745842545.0619967407.9922353.7995958282.251211.2124774.1458.2119978651.1423788.41137339126.481223.8927298.9469.8919989875.9524542.911904810061.991276.2729152.5521.55199911444.0824519.112611111152.861236.2631134.7534.29200013395.2324915.885673.712497.61284.53334152.6471.19200116386.0426179.69548.9815361.561247.6137595.2501.45200218903.6427390.811076.518527.181257.8642027.1499.81run;procprint;run;proccorrdata=anoprob;varyx1-x6;run;結(jié)果:表一分析：從相關(guān)陣看出，y與x2的相關(guān)系數(shù)偏小，x2是工業(yè)增加值，這說(shuō)明工業(yè)增加值對(duì)財(cái)政收入無(wú)顯著影響。■將數(shù)據(jù)做標(biāo)準(zhǔn)化處理，建立回歸方程程序2：procstandarddata=amean=0std=1out=out1;varyx1-x6;run;procprintdata=out1;run;procregdata=out1;modely=x1-x6;run;結(jié)果：右差分析涯自由度平方和均方「值Pr>r模型Fi17旳沖/亦了11<nnm謠差120.07721C.00644校正合計(jì)1慈1汽nnnnn均右根誤差u.u<ij27R右Cl&&57因量量均值2.80477E16制整R方0.9933翌異系數(shù)2.861804E16券數(shù)估訐值自由度tfri+ia泯羞1值Pr>1111ntorcropt12.53145E-160.01841a.aa1.0000xl1a.11vasCl15534a.750.4656X?1-U11GCjGou-h-；i-i7-:■--luuonnnx:310.87288Cl11D337.91<.00011Cl01659Cl07^16a.23a.8220x51Uu-IGCjuou:--7；7i-i1IU071口x：61Cl01022Cl02454a.420.6846表二因?yàn)閿?shù)據(jù)為標(biāo)準(zhǔn)化數(shù)據(jù)，所以方程中不含有常數(shù)項(xiàng)。所以有回歸方程為：Y=0.117.8x1-0.11696x2+0.87288x3+0.01659x+0.04690x5+0.01022x6由決定系數(shù)R方=0.9957，調(diào)整R方=0.9936，得回歸方程高度顯著。又有F=463.63，P<0.0001，表明回歸方程高度顯著，說(shuō)明x1,x2,x3,x4,x5,x6整體上對(duì)y高度顯著。在顯著性水平?二0.05時(shí)只有x2,x3通過(guò)了顯著性檢驗(yàn)，模型需要進(jìn)一步檢驗(yàn)?！霎惙讲顧z驗(yàn)采用等級(jí)相關(guān)系數(shù)法程序3:procregdata=out1;modely=x1-x6/r;outputout=z1r=residual;run;procgplotdata=z1;plotresidual*y;run;dataz2;setz1;absr=abs(residual);run;proccorrdata=z2spearman;varabsrx1-x6;run;圖一從殘差圖可看出，誤差項(xiàng)沒(méi)有呈現(xiàn)任何趨勢(shì)以及規(guī)律初步判斷不存在異方差。

簡(jiǎn)單虢計(jì)量M均值標(biāo)淮差中位數(shù)最小值最大值cibtsr190.043670.047770.032130.002100.1G073x11Rn1nnnnn-nnA4Ri-12QR7014AA41x21901.00000-0.54938-0.9D0601.78809x31g01.00000-0.23340-0.921f822.40429x41&01.uuuuuu.10&20-1.784761.37783x51901.00000-0.2600^1-0.^130024.05047xt>1yU1.uuuuuU.1b1J/一'厶J^JJI1.J4/UJSpearniari相關(guān)系數(shù)”N=19Prob>|r|underHO:Hho=0absrx1x2x3x4x5x6absr1ririrn'ii'ii'i!=iPi4740.0072ri71W70.3010riRi//A：0.005Ji'i4^ri7ri0.0372ri538S00.017斗I'I0.J364xli'i594740.00721□□□□□ri沙1肝0.2264ri口口汪寧冇<.0001ri口氣7耐只<.0001Ci卑777<.0001ri鮎X470.1200x2riyri^770.JD10rizPil竹0.2264100000ri旳旳a；0.22J5ri4"刊0.0712Fi3呵70.1斗2Driy4Hrii0.J108x3riri10.0053ri臼口汪：？?jī)?lt;.0001ri沙沙k0.22351riririririri口4刁耐1<.0001ri卑口47J0001ri37018o.11eex4ri4^ri7ri0.0372ri口冇7R5：<.0001ri0.0713riPi4!nfi1<.0001100000ri巧Ri4<.0001ri4^MriM0.0603x5ri□38600.0174i'i!^h77?<.0001ri349120.1420ri38347<.0001ri口時(shí)14<.0001100000ri^4/110.1517x6ri0.JUG4ri3S8420.1206i'i245610.31oeri^7m1汪0.11eci'i0.0603ri只切10.15171□□□□□表三程序4dataz3;n=19;dors=0.0072,0.3910,0.0053,0.0372,0.0174,0.3364;T=sqrt(n-2)*rs/sqrt(1-rs*rs);t1=tinv(0.975,n-2);output;end;run;procprintdata=z3;run;

SAS系統(tǒng)ObsnrsTt11190.594743050282.109822190.208770.880182.109823190.612283.192972.109824190.480702.260252.109825190.538602.635662.109826190.233330.98S352.10982表4可知模型存在異方差問(wèn)題.4.4自相關(guān)檢驗(yàn)程序5：procregdata=out1;modely=x1-x6/dw;run;結(jié)果：Durbin—WatsonD1.521觀(guān)測(cè)數(shù)19第一階自相關(guān)0.160表5DW值為1.521查表不能判斷是否存在自相關(guān)4.5.多重共線(xiàn)性檢驗(yàn)4.5.1方差擴(kuò)大因子法程序6

procregdata=out1;modely=x1-x6/vif;run;結(jié)果:拳數(shù)估計(jì)值變量自由度估計(jì)值標(biāo)準(zhǔn)逞差t值Pr>|t|方差BBfc1intercept12.53145E-160.018410.001.00000x110.117080.155340.750.465667.41892x21-0.116960.04867-2.400.03336.61761x310.872880.110337.91<.000134.00697x410.016590.072160.230.822014.54580x510.046900.023761.970.07191.57774x610.010220.024540.420.68461.68305表6可以看到xlx3x4的方差擴(kuò)大因子很大，分別為67.4189234.0069714.54580，超過(guò)10，說(shuō)明財(cái)政收入回歸方程存在多重共線(xiàn)性。4.5.2特征根判定法程序7procregdata=out1;modely=x1-x6/collinoint;run;共線(xiàn)性診斷（截距已謂整〉個(gè)數(shù)11偏差比例X1x2x3x4x5x61?：0203-OZOCO二20'1-10OD<OZcmE0Cl：0：3l0.013750.0130021二鈿183947A(TfTfTGI000003768AAiTin-4^-m：羽03M200287073:的1/?0：!i：.i)0001821301T!)10.008070001950000007840.52634257^720.00238ijuJ后L.UJJ1JLLIIJjJJ丿U./0.450CQ52.：71336339262.：03!：'0132'20.08224Cl.=2：7=0.遞近0-7-10G-一門(mén)兀巧1A4r^r~-蘋(píng)皿071723090472ri3734SA^=4'007742表7由上圖可知，條件數(shù)19.45707在xlx2和x3上的方差比率分別為0.992790.71723和0.90472,遠(yuǎn)超過(guò)50%，說(shuō)明兩變量高度共線(xiàn)。4.6消除多重共線(xiàn)性4.6.1后退法程序8procregdata=a;modely=x1-x6/selection=backward;run;結(jié)果向后消除:第0步所有變量已輸入:R方=0.9957和C(p)=7.0000方差分析源自由度平方和均方F值Pr>F模型6674884516112480753463.63<.0001誤差122911275242606校正合量參數(shù)估計(jì)值標(biāo)準(zhǔn)誤差I(lǐng)I型SSF值Pr>FIntercept-733.030475750.126543942.677580.020.9007x10.076530.101541378050.570.4656x2-0.016860.0070214010785.780.0333x30.797380.100781518587662.59<.0001

變量參數(shù)估計(jì)值標(biāo)準(zhǔn)II誤差型SSF值Pr>Fx41.377495.99041128280.050.8220x50.003910.001989449613.900.0719x61.353713.25216420350.170.6846條件數(shù)字的邊界:67.419,755.1向后消除:第1步變量x4已刪除:R方=0.9957和C(p)=5.0529方差分析源自由度平方和均方F值Pr>F模型5674871688134974338600.07<.0001誤差132924103224931校正合量參數(shù)估計(jì)值標(biāo)準(zhǔn)II型SS誤差F值Pr>FIntercept553.063221285.69944416220.190.6741x10.091750.074123447241.530.2376x2-0.017240.0065715516386.900.0209x30.789040.090551707971875.93<.0001x50.004110.0017212757425.670.0332x61.725692.71657907680.400.5363

條件數(shù)字的邊界:38.744,385.77向后消除:第2步變量x6已刪除:R方=0.9956和C(p)=3.4270方差分析源自由度平方和均方F值Pr>F模型4674780920168695230783.36<.0001誤差143014872215348校正合量參數(shù)估計(jì)值標(biāo)準(zhǔn)II型SS誤差F值Pr>FIntercept1343.77319315.04852391776018.190.0008x10.095490.072293757341.740.2077x2-0.017100.0064215269657.090.0186x30.789280.088601709027979.36<.0001x50.003850.0016411862445.510.0342條件數(shù)字的邊界:38.5,302.25向后消除:第3步變量x1已刪除:R方=0.9950和C(p)=2.9758方差分析源自由度平方均方F值Pr>F和模型3674405186224801729994.52<.0001誤差153390606226040校正合量參數(shù)標(biāo)準(zhǔn)II型SSF值Pr>F估計(jì)值誤差I(lǐng)ntercept1674.73790195.668761655910073.26<.0001x2-0.009380.00273266647511.800.0037x30.903970.018055668094812507.56<.0001x50.003740.0016811241594.970.0414條件數(shù)字的邊界:1.2135,10.382留在模型中的所有變量的顯著性水平都為0.1000。向后消除”的匯總步刪除的引入變量變量數(shù)偏模型C(p)F值Pr>FR方R方1x41x4“向后消除”的匯總步刪除的引入偏模型C(p)F值Pr>F變量變量數(shù)R方R方2x640.00010.99563.42700.400.53633x130.00060.99502.97581.740.2077表8參數(shù)都具有顯著性意義，最優(yōu)回歸子集模型的回歸模型為:Y=2.1435.4E-16-0.06508x2+0.98957x3+0.4486x54?6.2.逐步回歸程序9：procregdata=out1;modely=x1-x6/selection=stepwisevif;run;結(jié)果：方差分析自由度平右和均方F值Pr>F模型317.909965.969D99D4.52JJ001逞差lb0.090040.006D0校正合計(jì)1?；nnrnn均右根誤差U.07748RAULUDU因普早均值2C0477-1"調(diào)整F?方09940變異垂數(shù)2.762371E16拳數(shù)估計(jì)值變量自由瞪估計(jì)值標(biāo)淮謀羞1:值Pr>It|方差陶脹1rite廠(chǎng)匚ept1?14^4-001777000?moo0x21-0.055O50.01394-3刁0.O?371.C7611x310.90057U.U'L小5008<.UJU11.1/ULUx5100448600￡012004141的佔(zhàn)睡步迭擇第睡步迭擇第Z歩變呈已輸入X方=()9933和(p)=h甘個(gè)4方雀分析唾自由盅平方和F值Pr>F模型1/tJtJUlUS9400511!JIUI<UlU1溟差160.119900.00749校正臺(tái)計(jì)1并1?5nnnnn估計(jì)値標(biāo)淮誤畫(huà)11型朋r値Pr>rIriLerct?pL213J43E-1G001?8C8.67225E-310.001.0000X?-JUhH；l：iUlJ/J/1005551/41uU1hix3I.O'M8300237117631932353.34<.0001是件建字購(gòu)邊界一lcrjut；.門(mén)一ihmh曹早小已輸入Ft方一行加4"豐UC-P9/1>EJ自曲哇平右和均方1值IU>999994.02<.coni150.09004oooeoo西正合計(jì)1818.COOOO參數(shù)估計(jì)値標(biāo)淮逞差丨1型詼F値Pr>F1ntercept2.14354E16D017778.73007E310.001.CCCCx2-C06506DDIB940.07031--沁「x30.98957DD1D7615.052572507.56<.CCC10.04486332312C.029354.曠c.cm條件數(shù)字的邊界12135,10382留在模型中的所有變量的顯著性水平都為0.1500.

沒(méi)有其他變量滿(mǎn)足0.1500顯著性水平，無(wú)法輸入該模型?！爸鸩竭x擇”的3：總步輸入的姿量刪除的變量引入變量數(shù)偏R方C(p)F值Pr>F1x310.99030.990312.22521727.52<.00012x220.00310.99335.60947.410.01513x530.00170.99502.97584.970.0414表9參數(shù)都具有顯著性意義，最優(yōu)回歸子集模型的回歸模型為:Y=2.1435.4E-16-0.06508x2+0.98957x3+0.4486x54.7最佳子集回歸程序10procregdata=out1;modely=x1-x6/selection=cpaicadjrsq;run;結(jié)果：NumberinModeIC(p)R-SquareAIC模型中的變量32.97580.9650-93.6862x3x543.42700.9S56-93.9178x1x2x3x543.61610.9955-93.6308x2x3x4x544.47380.9952-92.3812x2x3x5x655.05290.0657-92.4986如y.2y5x6表10

基于C統(tǒng)計(jì)量x2x3x5是最優(yōu)子集，與逐步回歸選元結(jié)果相同。p4.8嶺回歸程序11：procregdata=out1outest=z4outvifmodely=x1-x6/ridge=0to1by0.1;plot/ridgeplot;run;procprintdata=z4;run;結(jié)果：O_MO結(jié)果：O_MO_TYP_DEP_RI_PCO_RMbDELE_VAR_DGEMIT_SE_s——1MODPARMy0.0EL1S80272MODRIDGy0.0EL1EVIF3MODRIDGy0.00.0EL1E80274MODRIDGy0.1EL1EVIF5MODRIDGy0.10.1EL1E36526MODRIDGy0.2EL1EVIF7MODRIDGy0.20.1EL1E86668MODRIDGy0.3Interceptx1x2x3x4x5x6y2.5310.1-0.10.80.00.00.0-4E-16171169672916646910210267.6.6134.14.1.51.6-4187610075457778301908452.5310.1-0.10.80.00.00.0-4E-1617116967291664691021020.70.981.01.71.01.0-1855058677060231251384.4920.3-0.20.50.10.00.0-7E-1620100946311375190831260.30.720.50.70.70.7-0930405925258127951615.1910.3-0.10.40.10.00.0-8E-1606587679615135601341460.20.570.30.40.60.6-_MODEL_TYPE__DEPVAR__RIDGE_PCOMIT__RMSE_Interceptx1x2x3x4x5x6yEL1EVIF062822852329327289160MODRIDGy0.3.0.25.4630.20.010.40.10.00.0-EL1E3093E-169256995366585991931412MODRIDGy0.4...0.10.480.20.20.50.5-EL1EVIF594131968914255216191MODRIDGy0.4.0.25.5790.2-0.10.40.10.00.0-EL1E7037E-1680053132187186282431959MODRIDGy0.5...0.10.400.20.20.40.4-EL1EVIF319938422157449413151MODRIDGy0.5.0.35.6250.2-0.10.30.10.00.0-EL1E057E-1668838009607406492851543MODRIDGy0.6...0.10.350.20.10.30.3-EL1EVIF135358046701824792111MODRIDGy0.6.0.35.6330.2-0.10.30.10.00.0-EL1E3762E-1658924667447426633181767MODRIDGy0.7...0.10.300.10.10.30.3-EL1EVIF001908768401327299156MODRIDGy0.7.0.35.6200.2-0.10.30.10.00.0-EL1E6664E-1649912935587326723451773MODRIDGy0.8...0.00.270.10.10.20.2-EL1EVIF899286554191925901164MODRIDGy0.8.0.35.5950.2-0.10.30.10.00.0-EL1E9323E-1641702623957156773661185Obs910111213141516171819O

b

s20212223_MODEL_TYPE__DEPVAR__RIDGE_PCOMIT__RMSE_Interceptx1x2x3x4x5x6MODRIDGy0.90.00.240.10.10.20.2EL1EVIF81628938403659557421MODRIDGy0.90.45.5620.2-0.00.30.10.00.0EL1E1766E-163429353250694679383393MODRIDGy1.00.00.210.10.00.20.2EL1EVIF74977824591831930173MODRIDGy1.00.45.5250.2-0.00.30.10.00.0EL1E4023E-162728548120671679396y11114760.8.-Q.4-oiii000102Q3040.50.6Q+06蟻骨點(diǎn)kP|Dt+-I-4scl+-b4m2十T-4■爲(wèi)十T-4■譽(yù)4f-1-+m5-+-i-tx6表11上-25F-I7s1-0.1l7s2啊忖附時(shí)?4憶M側(cè)癰ttD.MOEsfl42ae.七也s堅(jiān)圖2由嶺跡圖，當(dāng)K>=0.3，嶺跡曲線(xiàn)趨于穩(wěn)定，說(shuō)明K=0.3即可以滿(mǎn)足嶺回歸參數(shù)估計(jì)的均方誤差較小的要求，對(duì)應(yīng)的嶺回歸估計(jì)的回歸方程：Y=0.2925xl+0.01699x2+0.4536x3+0.1658x4+0.05991x5+0.01932x64.9主成分回歸程序12：procregdata=out1outest=z5outvif;modely=x1-x6/pcomit=1;run;procprintdata=z5;run;結(jié)果：MODELhpeDEPVARRIDGEPCOUI<Erromtxl:<2x5xSy1.：JEJ2.5314E-16:宓:|：：：?:m:心-■zI-:1-y■rA--.-1r；「，'4''I-K-■：■.：V_JF：：V■i：二二0.G澱-qm：i:;I?::：i<j；-■圖12Y=1.1814E-16+0.39282x1-0.19039x2+0.68593x3-0.06196x4+0.06018x5+0.02238x6由方