Dear Michael and Dingyuan Wang, > -----Original Message----- > From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Michael > Dewey > Sent: Thursday, April 18, 2019 11:25 AM > To: Dingyuan Wang <gumb...@aosc.io>; r-help@r-project.org > Subject: Re: [R] lm fails on some large input > > Perhaps subtract 1506705766 from y? > > Saying some other software does it well implies you know what the _correct_ > answer is here but I would question what that means with this sort of data- > set.
It's rather an interesting problem, though, because the naïve computation of the LS solution works: plot(x, y) X <- cbind(1, x) b <- solve(t(X) %*% X) %*% t(X) %*% y b abline(b) That surprised me, because I expected that lm() computation, using the QR decomposition, would be more numerically stable. Best, John ----------------------------------------------------------------- John Fox Professor Emeritus McMaster University Hamilton, Ontario, Canada Web: https://socialsciences.mcmaster.ca/jfox/ > > On 17/04/2019 07:26, Dingyuan Wang wrote: > > Hi, > > > > This input doesn't have any interesting properties except y is unix > > time. Spreadsheets can do this well. > > Is this a bug that lm can't do x ~ y? > > > > R version 3.5.2 (2018-12-20) -- "Eggshell Igloo" > > Copyright (C) 2018 The R Foundation for Statistical Computing > > Platform: x86_64-pc-linux-gnu (64-bit) > > > > > x = c(79.744, 123.904, 87.29601, 116.352, 67.71201, 72.96001, > > 101.632, 108.928, 94.08) > y = c(1506705739.385, 1506705766.895, > > 1506705746.293, 1506705761.873, 1506705734.743, 1506705735.351, > > 1506705756.26, 1506705761.307, > > 1506705747.372) > > > m = lm(x ~ y) > > > summary(m) > > > > Call: > > lm(formula = x ~ y) > > > > Residuals: > > Min 1Q Median 3Q Max > > -27.0222 -14.9902 -0.6542 14.1938 29.1698 > > > > Coefficients: (1 not defined because of singularities) > > Estimate Std. Error t value Pr(>|t|) > > (Intercept) 94.734 6.511 14.55 4.88e-07 *** y > > NA NA NA NA > > --- > > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > > > Residual standard error: 19.53 on 8 degrees of freedom > > > > > summary(lm(y ~ x)) > > > > Call: > > lm(formula = y ~ x) > > > > Residuals: > > Min 1Q Median 3Q Max > > -2.1687 -1.3345 -0.9466 1.3826 2.6551 > > > > Coefficients: > > Estimate Std. Error t value Pr(>|t|) > > (Intercept) 1.507e+09 3.294e+00 4.574e+08 < 2e-16 *** x > > 6.136e-01 3.413e-02 1.798e+01 4.07e-07 *** > > --- > > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > > > Residual standard error: 1.885 on 7 degrees of freedom Multiple > > R-squared: 0.9788, Adjusted R-squared: 0.9758 > > F-statistic: 323.3 on 1 and 7 DF, p-value: 4.068e-07 > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > --- > > This email has been checked for viruses by AVG. > > https://www.avg.com > > > > > > -- > Michael > http://www.dewey.myzen.co.uk/home.html > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.