多元線性回歸與非線性回歸

1、實驗三多元線性回歸與非線性回歸實驗目的：1、學會多元線性回歸的參數(shù)估計方法；2、掌握多元線性回歸的檢驗方法，包括擬合優(yōu)度檢驗、F檢驗和t檢驗，尤其是掌握調(diào)整的判斷系數(shù)和F檢驗的內(nèi)容；3、掌握非線性回歸的參數(shù)估計方法，尤其是能夠利用EViews軟件進行參數(shù)估計。實驗內(nèi)容：1、下表列出了某地區(qū)家庭人均雞肉年消費量Y與人均可支配收入X、雞肉價格P、豬肉價格的相關數(shù)據(jù)P，試利用這些資料，設定適當?shù)哪Ｐ瓦M行回歸分析。2年度Y（千克）X（元）19892.7839719902.9941319912.9843919923.0845919933.1249219943.3352819953.5656019963.

2、6462419973.6766619983.8471719994.0476820004.0384320014.1891120024.0493120034.07102120044.01116520054.27134920064.41144920074.67157520085.06175920095.01199120105.172258P（元/千克）P（元/千克）24.225.073.815.24.035.43.955.533.735.473.816.373.936.983.786.593.846.454.017.003.867.323.986.783.977.915.219.544.899.42

3、5.8312.355.7912.995.6711.766.37713.096.1612.985.8912.806.6414.101）、計算相關系數(shù)Group:UMITTLEDWorkfile:BOOICL:Boakl_XviewPfQCObjectPrintMameFreezeSampleSheetStatsSpecCorrelationYXP1P2Y1.0000000.9444230.8080080.897636X0.9444331.0000000.9157320.943916P10.8080080.9157221.0000000.963475P20.8976360.9439160.9634

4、751.000000(2)繪制散點圖0EViewsFileEditObjectViewProcQuickOptiscatyxscatyp1scatyp22建立模型EquationEstimationSpedficationOptionsI-礙II-wfi-1(=Equation:UhnTTLEDWorlcffFe:BOOKl:Bookl_XviewProcObjectPrintNameFreezeEstimateForecastSttsResidsDependentVariable:¥Method:LeastSquaresDate:11/13/14Time:21:21Sample:1

5、9392010Includedobservations:22VariableCoefficientStd.Errort-StatisticProb.C3.9055980.31543312379740.0000X0.00120.20.0002105.7122880.0000P1-0-59384120.137330-4.3066480.0004-P20.1872980.05435334459470.0029R-squared0.946957Meandependentvar3.906318AdjustedR-squared0.93S117S.D.dependentvar0.694512S.E.ofr

6、egression0.172769Akaikeinfocriterion-0.510761Sumsquaredresid0.53723:2Schwarzcriterion-0312389Loglikelihood9.618369Hannan-Ciuinncriter.-0.464030F-statistic107.1168Durbin-Watsonstat1122907Prob(F-statistic)0.0000002、為了度量投資和勞動投入之間的替代彈性當今著名的CES（恒定替代彈性）模型形式設定為In（V/L）=In卩+卩InW+£01其中，V/L表示單位勞動的附加值，L表示投

7、入的勞動，W表示實際工資率。系麴i表示勞動與資本之間的替代彈性。用下表給出的數(shù)據(jù)，驗證估計的彈性1是.324，并且它和1在統(tǒng)計上無顯著差異。工業(yè)行業(yè)In(V/L)InW小麥面粉3.69732.9617食糖3.4795涂料與油漆水泥4.00043.66092.85323.11583.0371玻璃陶瓷三夾板棉紡品毛紡品3.23213.34183.43083.31583.50622.87272.97452.82873.08883.0086大麻紡織3.23522.9680化纖鋁制品鐵與鋼自行車縫紉機3.88233.70393.77163.66013.75543.09093.08813.22563.10

8、253.1354F4eEditObjectViewProcQuickOptionsWindowHelpLSxcy=Equation:UhnHLEDWorld咤BOOK2:Book2_XviewPracObjectPrintNameFreezeEstimateForecastSttsReldsDependentVariable:XMethod:LeastSquaresate:11/1S/UTime:21:30Sample:115Includedobservations:15VariableCoefficientStd.Errort-StatisticProb.C-04251571.34739S-

9、0.3155410.7574-Y1.324m0.U53562.9731580.0108R-squared0404753Meandependentvar3.57S220AdjustedR-squared0.35S965S.D.dependentvar0.236325S.E.ofregression0.109213Akaikeinfocriterion-0363326Sumsquaredresid0465418Schwarzcriterion-0.273919Loglikelihood4.762441Hannan-Ciuinncriter.-0.369331F-statistic3.839669D

10、urbin-Watsonstat1.816336Prob(F-statistic)0.010701WaldTest!Coefficientrestrictionsseparatedby匚ommasC図=1ExamplesClJ=OfC®=2*C(4)OKCancel=Equation:UhTTHLEDWorkfile:BOOK2:Book2viewProcObjectPrintNameFreezeEstimateForecastStatsRe5idsWaldTestEquation:UntitledTestStatisticValuedfProbabilityt-statistic0.727763130.4797F-statistic0.529638(1.13)0.4797C