- > x<-c(0.10,0.11,0.12,0.13,0.14,0.15,0.16,0.17,0.18,0.20,0.21,0.23)
- > y<-c(42.0,43.5,45.0,45.5,45.0,47.5,49.0,53.0,50.0,55.0,55.0,60.0)
- > lm.sol<-lm(y ~ 1+x)
- > summary(lm.sol)
- Call:
- lm(formula = y ~ 1 + x)
- Residuals:
- Min 1Q Median 3Q Max
- -2.0431 -0.7056 0.1694 0.6633 2.2653
- Coefficients:
- Estimate Std. Error t value Pr(>|t|)
- (Intercept) 28.493 1.580 18.04 5.88e-09 ***
- x 130.835 9.683 13.51 9.50e-08 ***
- ---
- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
- Residual standard error: 1.319 on 10 degrees of freedom
- Multiple R-squared: 0.9481, Adjusted R-squared: 0.9429
- F-statistic: 182.6 on 1 and 10 DF, p-value: 9.505e-08
那么我们如何由线性回归的结果lm.sol直接给出来残差的自由度呢?当然后来他的书里面也提到了用
- lm.sol$da.residual
现在我有点不明白的是如何确定用
- lm.sol$da.residual
即可,从哪里可以看出来?
谢谢!


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