R語言代碼試題答案步驟

1、R version (2017-11-30) - "Kite-Eating Tree"Copyright (C) 2017 The R Foundation for Statistical ComputingPlatform: x86_64-w64-mingw32/x64 (64-bit)R是自由軟件，不帶任何擔保。在某些條件下你可以將其自由散布。用'license()' 或 'licence()' 來看散布的詳細條件。R是個合作計劃，有許多人為之做出了貢獻.用 'contributors()'來看合作者的詳細情況用'

2、citation()'會告訴你如何在出版物中正確地引用 R 或 R程序包。用 'demo()' 來看一些示范程序，用 'help()' 來閱讀在線幫助文件，或 用'()' 通過 HTML瀏覽器來看幫助文件。用'q()' 退出 R. 原來保存的工作空間已還原 > h=("",header=true)Error in (file = file, header = header, sep = sep, quote = quote,找不到對象 'true'> h=("&qu

3、ot;,header=TRUE)地區(qū) x1 x2 x3 x4 x5 x6 x7 x8 x9 y96比乙6乙9區(qū)址怦6£6九6 09" 09西卑三9298921 0以6L 9門片96叩999怦0L 66叩£66廠M獸陀09091 80962 Z89L ZLL 旳衣旳9L 九09 |間 £2 CZ99L t7L68C86m SOU ZZH 6222 0Z89 ¥f重7ZLQvnzzese sse osei £66isgi §989999卑蝕比znS96ZS98C9e 929188ZZCL£999MJOS96CSS960

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6、98H7»8L OLCL COL 抄0乙 6089 占以 9 LVLLV988C9L999V SZ6L 西叩 >891 OCZS£9西早毒M9乙比即8S9Ce9隠舛 9091 906 6£怦 6291998C歴E>吃L>899£8998C X）即"0L 2091 眇門14少菲風£陀00乙£Z 比6怦69 V9ZZ 9991 >981 188 L舉工2 9旳陀 9Zi7Z8 28 969C 8991 LZ6L 6C9S 9C9Z 車菲(II H erop-6X + gx + x + gx + gx +

7、寸x + gx +CXIX + LXA H E_nlu04)lu_=eoE- A (lluerop-6x+8x+2.x+9x+gx+寸 X+2X+CXIX+XA)lu_ulu- A CXI68CL 96 卜 me 9卜 9寸寸 L8CXIL 8CXI0L 卜9L LOOCXI6CCXI9 mso 卜 90 寸 L 寸 6C9C 9"寸卜寸 9 L9 L "90 L "6 L L 9卜 8 L 69 卜寸w00 9 寸 eCXI廠soe "8 寸9寸卜 60 L 906CXIeCXILCXILg L 卜 99 寸«*6CXI 卜寸 8CXIL 8

8、 卜6LCXI6 卜 9卜 “ 88"L 090L 88CXILO9LCXI09 寸 8CXI emegL 寸 卜oe寸 6卜0cxlcxlLcxlLcxlcxleL68卜二 ggg 且崖 P 寸 8LLL 9C6CXICXI90卜 L9 099 卜9 寸 9 寸8CXI9CL 8L99B且 9CXIin(II H eropgx + x + gx + gx + 寸x + gx +CXIX + LXA H E_nE04)E_6X_eo(E-)AJEEEns A9X(Id O2U-)Min 1Q Median 3Q MaxCoefficients:Estimate Std. Error

9、t value Pr(>|t|)(Intercept) +02 +03x1+00x2+00x3+00x4x5+00x6x7x8+01+01x9+01+02Signif. codes: 0* ' *' *' .' ' 1Residual standard error: on 21 degrees of freedomMultiple R-squared: , Adjusted R-squared:F-statistic: on 9 and 21 DF, p-value: <> pre=(lm)> res=residuals(lm)&

10、gt; sd(res)1 > res=residuals(lm)> dy=step(lm)Start: AIC=y x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9Df Sum of Sq RSS AICx4121 3184326x9117149 3201454x7117700 3202005x8154295 3238599x6189586 3273891none>3184305x312662593 5846898x214561056 7745361x519377500x11Step: AIC=y x1 + x2 + x3 + x5 + x

11、6 + x7 + x8 + x9Df Sum of Sq RSS AIC- x9 1 17428 3201754 - x7 1 18563 3202889- x8 1 54437 3238763 - x6 1 91813 3276139<none> 3184326x3129361306120456x2154679418652267x519393345x11Step: AIC=y x1 + x2 + x3 + x5 + x6 + x7 + x8Df Sum of SqRSS- x71346343236387- x61748003276554- x81821503283904<n

12、one>3201754- x3130553536257107- x2157258368927590- x519382624- x11Step: AIC=y x1 + x2 + x3 + x5 + x6 + x8Df Sum of Sq RSS AIC- x8 1 70813 3307201- x611527773389165<none>3236387- x3155012848737672- x218895049- x519458098- x11Step: AIC=y x1 + x2 + x3 + x5 + x6Df Sum of Sq RSS AIC- x6113754034

13、44741<none>3307201- x3157710639078264- x218871193- x519473521- x11Step: AIC=y x1 + x2 + x3 + x5Df Sum of Sq RSS AIC<none> 3444741 - x3 1 5717883 9162624- x2 1 - x5 1- x1 1> summary(dy)Call:lm(formula = y x1 + x2 + x3 + x5, data = h)Residuals:Min 1Q Median 3Q MaxCoefficients:Estimate S

14、td. Error t value Pr(>|t|)(Intercept) * x1 x2 x3 x5Signif. codes: 0* ' *' *' .' ' 1Residual standard error: 364 on 26 degrees of freedomMultiple R-squared: , Adjusted R-squared:F-statistic: on 4 and 26 DF, p-value: <> newdata=(x1=5200,x2=2000,x3=1100,x4=1000,x5=1300,x6=4

15、5000,x7=34000,x8=,x9=> predict(dy,newdata,interval="confidence") fit lwr upr1 >以卜我們用線性億的乘住誤差做模熨擬合C-D牛產(chǎn)用數(shù)» 尸36243962.9 4124.2 4330.6 46235()802 5977.3 68363 7305.4 7983.2 8385.9 8049.78564.3 9653.5 11179.9 12673.0 13786.9 14724.3 15782.8 16840.6 17861.6 18975.9 20604.7 22256.0 24

16、247.0P;» K<1377.9 1446.7 1451 5 1408.1 1536 9 1716.4 2057 7 2582.2 2754.0 2884.3 3086 8 2901.52975.4 3356$ 41U4.2 5487.9 5679 0 6012.() 6246.5 6436 0 67367098.9 7510.5 X567.3 9764.9) ; » L二40152 41024 42361 43725 45295 46436 48197 49873 51282 52783 54334 55329 647496545 66152 66K0S 6745

17、5 6X065 6X950 69820 7()637 71394 72OJJ5 73025 73740f; »y1=log(y);» xl=log(K);» x2-Iog(L);» x=(oncs(25.1) xl x2;Ia>：» h,hinr5raTsrcoplor(rjinr)b = .1.78540.80110.40161.19780.91670.7554bint 二4.76870.68550.0478stats = I.Oe-t-003 0.00101.80550 » exp(-1.7854) ans =0.1677&

18、#187; v-36243962.9 4124.2 4330.6 4623.1 5080.2 5977.3 6836.3 7305.4 7983.2 8385.9 8049.785643 9653.5 11179.9 12673.0 13786.9 14724.3 1 5782.8 16840.6 17861.6 18975.9 20604.722256.0 24247.0；>> y | 二 1.7X5440X011 1+0 4() 16X2;» y2=cxp(yl);» e=y-y20.250208390.18160.2274()(M6IMl 3450(12X

19、3-0.060.20510.52680.81951.5361c -I .Oof003 * (-0.25100.1014-0.0037-0.1560-(1.14(X)().16690.0364-1.7U7-1.0550-0.8671-0.37750.95590.5003)參數(shù)參數(shù)估計色參數(shù)的置信區(qū)間A-1.7854-4.7687J.1978a0.8011I0.6855A916700.4016l().()47X,0.7554JR2 = 1.0000F = 1805.5p = 0.0000得兩個彈件系數(shù)為a-(). KOI I4()16.龐金的貢獻率大T勞功者旳貢獻軋 規(guī)棋報酬 a + “R.202

20、7>l農(nóng)示規(guī)模報酬遞增，效率系A=/ X-1=0. lG77eM中系數(shù)的顯若性概率P俏=0.000顯著件軟強。得乘侑課幷頂?shù)腃-I)牛產(chǎn)悶數(shù)為A"0.4016uO.I677KL2、加性誤差項，模型形式為y = AK"Z?+£對加性誤差項模型，不能通過變量變換轉(zhuǎn)化成線性模型.只能用非線性最小一乘求解未知參 數(shù)。以上面乘性謀差項的參數(shù)為初值做非線性最小二乘首先編寫一個M文件Huaxuel.mfunction yhat=huaxuel (beta,x)bl=beta( 1 );b2=bcta(2);b3=beta(3);xl=x(:):x2 二 x(：2);yha

21、t-b 1*(x1 Ab2)*(x2Ab3)然后在MATI AB命令窗輸入：» xl =1377.9 1446.7 1451 5 1408.1 1536.9 1716.4 2057.7 2582.2 2754.0 2884.3 3086.8 2QO1.52075.4 ； » x2-4O152 41024 42361 43725 45295 46436 48197 49873 51282 52783 54334 55329 64749 65491 66152 668()8 67455 68()65 68950 69820 70637 71394 72085 73025 737

22、4():» y-3624.1 3962.9 4124.2 4330.6 46235080.2 5977.3 6836.3 7305.4 7983.2 8385.9 8049.7 85643 9653.5 11179.9 12073.0 13786.9 14724.3 15782.8 16840.6 17861.6 18975.9 20604.7 22256.0 24247.0;» x=xl x2;» beta二卜 1.7X54 0.8011 ().4016J;» |bctahat.fj|-nlinfit(x.y/huaxuelbcta);(2) DW檢驗

23、第一步：計算出回歸估計式的殘差“£ (勺-勺-|)2人第二步：定義DW統(tǒng)計星為DW二 ,其中 =V, -(t=l,2, .,n)a茁/=2認為5?/與X-i2近似相籌, 畑2心2n oE e：t=2DW 亠2 (1-/7 )ei= l.()cHX)350.251()-0.1014 O.(X)370.2502().18390.18160.22740.1560-0.140()0.16690.03640.0461-0.13450.0283-0.0396-1.7117-1.05500.8671-0.37750.20510.52680.81951.53610.9559;» ej=l0

24、e+003 *-0.1014 CI.OO370.2502(LIX390.18160.2274-0.156()-0.14000.16690.03640.0461-0.13450.0283-0.03961.7117 1.055() 0.K67I-037750.20510.52680.81951.5361().95590.5(X131：» vancr(eitej) » sum(ei.*ej)/sum(ei.A2)ans =0.7212» 2*( I -sum(ei.*ej)/sum(ei.A2)0.5576» sum( (ei-ej).2)/sum(ei.A2

25、) ans =0.57725 即有 OVDM二0.5772 V dL = 1.29.且杳衷得出，當n=25A2時.血二L29,血二町以認為溟笫項存在止自相關> h=ts("",header=TRUE)> hTime Series:Start = 1End = 56Frequency = 1X78 1, -58 2, 53 3, -63 4, 13 5, -6 6, -16 7, -14 8, 3 9, -74 10, 89 11, -48 12, -14 13, 32 14, 56 15, -86 16, -66 17, 50 18, 26 19, 59 20,

26、 -47 21, -83 22, 2 23, -1 24, 124 25, -106 26, 11327, -7628, -4729, -3230, 3931, -3032, 633, -7334, 1835, 236, -2437, 2338, -3839, 9140, -5641, -5842, 143, 1444, -445, 7746, -12747, 9748, 1049, -2850, -1751, 2352, -2 53, 4854, -13155, 6556, -17> plot(h,type="o")> local(pkg <- (sor

27、t(.packages = TRUE),graphics=TRUE)+ if(nchar(pkg) library(pkg, =TRUE)Warning message:程輯包 urca '是用 R版本 來建造的> adf=(h),type=c("drift"),selectlags=c("AIC")> summary(adf)# Augmented Dickey-Fuller Test Unit Root Test #Test regression driftCall: lm(formula = + 1 + Min 1Q Media

28、n 3Q MaxCoefficients:Estimate Std. Error t value Pr(>|t|)(Intercept)Signif. codes: 0* ' *' *' .' ' 1Residual standard error: on 51 degrees of freedomMultiple R-squared: , Adjusted R-squared:F-statistic: on 2 and 51 DF, p-value: <Value of test-statistic is:Critical values fo

29、r test statistics:1pct 5pct 10pct> ar=sarima(h,1,0,4,details=F)> ar$fitCall: stats:arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D,Q), period = S), xreg = xmean, = FALSE, = list(trace = trc,REPORT = 1, reltol = tol)Coefficients:ar1 ma1 ma2 ma3 ma4 xmean sigma2 estimated as

30、1850: log likelihood = , aic =$degrees_of_freedom1 50$ttableEstimate SEar1ma1ma2ma3ma4xmean$AIC$AICc 1$BIC1> ma=sarima(h,0,1,1,details=F)> ma$fitCall: stats:arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D,Q), period = S), xreg = constant, = list(trace = trc, REPORT = 1, reltol = tol)Coefficients:ma1 constant sigma2 estimated