回归方程的显著性检验.doc

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1、多元线性回归以水资源短缺为例clearall; clc; x4=[0.42420.28850.26630.40610.38500.43620.42160.29990.42890.43470.23910.39790.46920.24900.21820.50390.33660.50890.24690.41830.15780.18710.21300.17860.20420.23740.25740.27180.26410.2423]'; x5=[0.64430.84820.84210.76770.84210.58200.26970.51860.25800.58600.65070

2、.57930.60490.53140.54230.55770.51510.50500.48290.46340.49170.43940.46370.41300.36770.35970.35180.34110.33040.3198]'; x6=[1.40371.34511.19271.35681.09801.40431.68010.96801.36851.37151.34511.20541.16241.51511.49261.42321.34611.14871.08431.05891.03151.0270.89870.73260.82050.75220.66420.6056

3、0.56660.5079]'; x7=[0.25820.29180.25400.26700.27880.23730.25930.42410.42890.37810.38100.41590.43890.64860.56650.61260.69530.54940.65570.72070.75020.79100.72660.68530.80340.79160.85660.90380.98061.0810]'; x8=[0.31660.28540.28540.28540.28540.28540.28540.32460.32520.35500.36920.39760.40370.

4、43070.44490.45990.46400.47200.48590.50550.51540.51830.55070.57610.58030.59510.59640.60350.61060.6305]'; x10=[0.00170.00170.00190.00190.00190.00190.00190.00200.00200.00200.00200.00230.00230.00040.00040.00190.00450.00450.00450.00450.00450.00980.01090.01370.01630.01930.02450.02500.02670.026

5、9]'; Y=[0.13780.72880.72550.31560.38350.0196700.305400.09280.70930.157900.7290.7830.00390.442200.57020.07760.86360.74540.62970.61440.57050.43550.37180.32180.36050.447]'; X=[x4,x5,x6,x7,x8,x10]; [b,se,pval,inmodel,stats,nextstep,history]=stepwisefit(X,Y,'penter',0.10,'display','off'); %自变

6、量的筛选和模型参数估计信息 inmodel pval b0=stats.intercept b ALLp=stats.pval%回归方程显著性整体检验信息 rmse=stats.rmse P=stats.PVAL%回归方程显著性分别检验信息