Dear Jinsong,
Why do you say that the coefficients are wrong? The slope is 1 and the
intercept 0 (within rounding) -- Isn't this what you intended?
John
On Fri, 6 Feb 2004 08:50:36 -0800 (PST)
Jinsong Zhao <jinsong_zh at yahoo.com> wrote:> Dear all,
>
> The following is a example that I run and hope to get a linear model.
> However, I find the lm() can not give correct coefficients for the
> linear model.
>
> I hope it's just my own mistake. Please help. TIA.
>
> Regards,
>
> Jinsong
>
> > x
> [1] 3.760216 3.997288 3.208872 3.985417 3.265704 3.497505 2.923540
> 3.193937
> [9] 3.102787 3.419574 3.169374 2.928510 3.153821 3.100385 3.768770
> 3.610583
> [17] 3.588902 3.180961 3.415033 3.595447 2.826521 3.283875 3.125694
> 3.558275
> [25] 4.625191 3.735673 4.387571 4.884388 3.067845 2.993892 3.068684
> 4.166771
> [33] 4.680322 4.103344 4.340546 3.685950 4.026451 4.161470 3.696610
> 4.026815
> [41] 3.854591 3.399321 3.492201 3.479075 4.417633 3.579751 3.433551
> 3.248359
> [49] 2.874979 3.123579 3.131758 3.447368 3.086075 3.558168 4.537077
> > y
> [1] 4.431 4.560 2.920 4.481 3.295 3.679 2.779 2.654 2.837 3.664
> 3.421
> 2.693
> [13] 2.624 3.057 4.633 3.807 3.886 3.011 3.873 3.717 2.077 3.324
> 2.064
> 3.390
> [25] 4.170 3.232 3.114 4.701 3.746 2.880 3.723 4.015 4.881 4.483
> 4.762
> 3.834
> [37] 4.321 3.837 3.624 4.306 3.466 3.492 3.502 3.510 4.236 3.286
> 3.657
> 3.218
> [49] 2.840 3.011 3.417 3.625 3.524 3.390 4.296
> > g <- lm(y ~ x)
> > summary(g)
>
> Call:
> lm(formula = y ~ x)
>
> Residuals:
> Min 1Q Median 3Q Max
> -1.2736 -0.2094 0.0098 0.2654 0.8642
>
> Coefficients:
> Estimate Std. Error t value Pr(>|t|)
> (Intercept) -1.274e-15 4.027e-01 -3.16e-15 1
> x 1.000e+00 1.113e-01 8.982 3.13e-12 ***
> ---
> Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 `
' 1
>
> Residual standard error: 0.4179 on 53 degrees of freedom
> Multiple R-Squared: 0.6035, Adjusted R-squared: 0.596
> F-statistic: 80.68 on 1 and 53 DF, p-value: 3.128e-12
>
>
>
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