spss非線性回歸分析

1、課程名稱 實(shí)用統(tǒng)計(jì)軟件 實(shí)驗(yàn)項(xiàng)目名稱 非線性回歸分析 實(shí)驗(yàn)成績(jī) 指導(dǎo)老師（簽名 ） 日期 2011-9-23 一實(shí)驗(yàn)?zāi)康?掌握非線性回歸的基本原理和算法；2能夠用SPSS軟件應(yīng)用非線性回歸模型解決實(shí)際問(wèn)題。二. 實(shí)驗(yàn)內(nèi)容與要求 1根據(jù)數(shù)據(jù) 金屬?gòu)?qiáng)度測(cè)試.sav利用曲線參數(shù)估計(jì)法分析金屬?gòu)?qiáng)度（y）與溫度（x）之間的關(guān)系。2實(shí)現(xiàn)書上 P189 中的研究問(wèn)題。第一步要選中所有的模型，然后根據(jù)R-square 和擬合曲線標(biāo)準(zhǔn)選擇模型！并且要預(yù)測(cè)到2010年的數(shù)據(jù)！三實(shí)驗(yàn)步驟1模型選擇（標(biāo)準(zhǔn)：R-square 以及擬合曲線的比較）2所選擇模型的擬合優(yōu)度（R-square、擬合曲線）3所選擇模型的回歸方程

2、（回歸系數(shù)的估計(jì)值）4所選擇模型的檢驗(yàn)問(wèn)題（模型方差分析表：模型顯著性F檢驗(yàn)、回歸系數(shù)非零T檢驗(yàn)）5保存關(guān)心的統(tǒng)計(jì)數(shù)據(jù)（預(yù)測(cè)值、殘差值、預(yù)測(cè)值的置信區(qū)間）具體操作參見(jiàn)課件 非線性回歸分析.PPT四. 實(shí)驗(yàn)結(jié)果（數(shù)據(jù)與圖形）與分析1.Model Summary and Parameter EstimatesDependent Variable:強(qiáng)度EquationModel SummaryParameter EstimatesR SquareFdf1df2Sig.Constantb1b2b3Linear.67412.39116.013.719-.002Logarithmic.92573.7121

3、6.0002.518-.424Inverse.983346.05116.000-.09155.466Quadratic.94441.91025.0011.171-.0068.416E-6Cubic.993186.30234.0001.485-.0123.409E-5-3.144E-8Compound.992760.86116.0001.324.991Power.93281.77216.0002.136E3-1.833S.69313.53516.010-3.356200.730Growth.992760.86116.000.281-.009Exponential.992760.86116.000

4、1.324-.009Logistic.992760.84016.000.7551.009The independent variable is 溫度.圖中看出Cubic，Compound，Growth，Exponential和Logistic較高，其中Cubic最高，所以選擇三次函數(shù)擬合。觀察得，圖形更接近Cubic和Exponential兩種曲線。Cubic函數(shù)在500處為0，有明顯差異。ANOVASum of SquaresdfMean SquareFSig.Regression14.368114.368760.861.000Residual.1136.019Total14.4827The

5、 independent variable is 溫度.CoefficientsUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBeta溫度-.009.000-.996-27.584.000(Constant)1.324.12810.382.000The dependent variable is ln(強(qiáng)度).CoefficientsaModelUnstandardized CoefficientsStandardized CoefficientstSig.95% Confidence Interval

6、for BCorrelationsBStd. ErrorBetaLower BoundUpper BoundZero-orderPartialPart1(Constant).719.1444.982.002.3661.072溫度-.002.001-.821-3.520.013-.003.000-.821-.821-.821a. Dependent Variable: 強(qiáng)度0.366,1.072-0.003,02.Model Summary and Parameter EstimatesDependent Variable:社會(huì)消費(fèi)品零售總額EquationModel SummaryParame

7、ter EstimatesR SquareFdf1df2Sig.Constantb1b2b3Linear.836137.490127.000-1.372E42.325E3Logarithmic.52730.083127.000-2.442E41.854E4Inverse.1846.104127.0202.764E4-4.756E4Quadratic.987953.866226.0006.756E3-1.639E3132.133Cubic.9951.816E3325.000230.765768.904-65.2004.385Compound.9955.654E3127.0001.368E31.1

8、52Power.856160.241127.000446.2581.322S.43120.448127.0009.905-4.068Growth.9955.654E3127.0007.221.142Exponential.9955.654E3127.0001.368E3.142Logistic.9967.339E3127.000.001.856Logistic，Cublic，Compound，Growth，Exponential擬合度較高。觀察得，Cublic和Logistic曲線更接近觀察值。Model Summary and Parameter EstimatesDependent Var

9、iable:社會(huì)消費(fèi)品零售總額EquationModel SummaryParameter EstimatesR SquareFdf1df2Sig.Constantb1b2b3Cubic.9951.816E3325.000230.765768.904-65.2004.385CoefficientsUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBetaCase Sequence2324.553198.246.91411.726.000(Constant)-13724.6833404.981-4.031.000CoefficientsaModelUnstandardized CoefficientsStandardized CoefficientstSig.95% Confidence Interval for BBStd. ErrorBetaLower BoundUpper