[R] lm fails on some large input

[Dingyuan Wang]

The final goal is to make two lines and find the intersection point.
I don't want to argue more about the reason.

The tol suggestion is reasonable, and I'll take that.

2019/4/19 4:12, Jeff Newmiller:
> The fact that you think x~y is interchangeable with y~x suggests to me that you will have a difficult time convincing R Core that this is a bug. I recommend that you take at leastan upper division college course in linear regression first.
> 
> On April 18, 2019 9:35:55 AM PDT, Dingyuan Wang <gumblex using aosc.io> wrote:
>> I just want to make a line out of timestamps vs some coordinates, so
>> y~x
>> or x~y doesn't matter.
>>
>> Yes, I know the answer. When trying R, I'm surprised that R can't solve
>>
>> that either. I first noticed that PostgreSQL can't solve it, and found
>> that they fixed that in pg 12.
>>
>> https://www.postgresql.org/message-id/153313051300.1397.9594490737341194671%40wrigleys.postgresql.org
>>
>> Therefore I come to ask whether someone know how to fix this in R, or I
>>
>> must submit it as a bug?
>>
>> 2019/4/18 23:24, 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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>>>
>>
>> ______________________________________________
>> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
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>> and provide commented, minimal, self-contained, reproducible code.
>