[R] lm fails on some large input

[Michael Dewey]

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.

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
> 
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html