[R] lm fails on some large input

[Dingyuan Wang]

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