[R] Axis with inverse logarithmic scale
John Fox
j|ox @end|ng |rom mcm@@ter@c@
Tue Jul 28 16:47:35 CEST 2020
Dear Martin,
On 7/28/2020 10:17 AM, Martin Maechler wrote:
>>>>>> Martin Maechler
>>>>>> on Tue, 28 Jul 2020 15:56:10 +0200 writes:
>
>>>>>> John Fox
>>>>>> on Mon, 27 Jul 2020 12:57:57 -0400 writes:
>
> >> Dear Dileepkumar R,
> >> As is obvious from the tick marks, the vertical axis is not log-scaled:
>
> >>> log10(99.999) - log10(99.99)
> >> [1] 3.908865e-05
> >>> log10(99) - log10(90)
> >> [1] 0.04139269
>
>
> >> That is, these (approximately?) equally spaced ticks aren't equally
> >> spaced on the log scale.
>
> >> The axis is instead apparently (at least approximately) on the logit
> >> (log-odds) scale:
>
> >>> library(car)
> >> Loading required package: carData
> >>> logit(99.999) - logit(99.99)
> >> [1] 2.302675
> >>> logit(99) - logit(90)
> >> [1] 2.397895
>
> > Small remark : You don't need car (or any other extra pkg) to have logit:
>
> > logit <- plogis # is sufficient
>
> > Note that the ?plogis (i.e. 'Logistic') help page has had a
> > \concept{logit}
>
> > entry (which would help if one used help.search() .. {I don't;
> > I have 10000 of packages}),
> > and that same help page has been talking about 'logit' for ca 16
> > years now (and I'm sure this is news for most readers, still)...
>
> but now I see that car uses the "empirical logit" function,
> where plogis() provides the mathematical logit():
Not quite the empirical logit, because we don't know the counts, but a
similar idea when the proportions include 0 or 1. Also, logit()
recognizes percents as well as proportions, and so there's no need to
convert the former to the latter.
>
> The former is typically needed for data transformations where
> you don't want to map {0,1} to -/+ Inf but rather to finite
> values ..
>
> So I should stayed quiet, probably..
Well, I wouldn't go so far as that.
Best,
John
>
> Martin
>
>
> >> You can get a graph close to the one you shared via the following:
>
> >> library(car) # repeated so you don't omit it
>
> > .. and here you need 'car' for the nice probabilityAxis(.) ..
>
> >>> logits <- logit(y_values)
> >>> plot(x_value, logits, log="x", axes=FALSE,
> >> + xlim=c(1, 200), ylim=logit(c(10, 99.999)),
> >> + xlab="Precipitation Intensity (mm/d)",
> >> + ylab="Cumulative Probability",
> >> + main="Daily U.S. Precipitation",
> >> + col="magenta")
> >>> axis(1, at=c(1, 2, 5, 10, 20, 50, 100, 200))
> >>> probabilityAxis(side=2, at=c(10, 30, 50, 90, 99, 99.9, 99.99,
> >> 99.999)/100)
> >>> box()
>
> >> Comments:
>
> >> This produces probabilities, not percents, on the vertical axis, which
> >> conforms to what the axis label says. Also, the ticks in the R version
> >> point out rather than into the plotting region -- the former is
> >> generally considered better practice. Finally, the graph is not a
> >> histogram as the original title states.
>
> >> I hope this helps,
> >> John
>
>
> >> --------------------------------------------
> >> John Fox
> >> Professor Emeritus
> >> McMaster University
> >> Hamilton, Ontario, Canada
> >> web: https://socialsciences.mcmaster.ca/jfox/
>
> >> On 7/27/2020 11:56 AM, Dileepkumar R wrote:
> >>> I think the attached sample figure is not visible
> >>> Here is the sample figure:
> >>> https://drive.google.com/file/d/16Uy3JD0wsEucUv_KOhXCxLZ4U-3wiBTs/view?usp=sharing
> >>>
> >>> sincerely,
> >>>
> >>>
> >>> Dileepkumar R
> >>>
> >>>
> >>>
> >>>
> >>> On Mon, Jul 27, 2020 at 7:13 PM Dileepkumar R <dileepkunjaai using gmail.com>
> >>> wrote:
> >>>
> >>>> Dear All,
> >>>>
> >>>> I want to plot a simple cumulative probability distribution graph with
> >>>> like the attached screenshot.
> >>>> But I couldn't fix the y-axis scale as in that screenshot.
> >>>>
> >>>> My data details are follows:
> >>>>
> >>>> y_values
> >>>> =c(66.78149,76.10846,81.65518,85.06448,87.61703,89.61314,91.20297,92.36884,
> >>>> 93.64070,94.57693,95.23052,95.75163,96.15792,96.58188,96.97933,97.29730,
> >>>> 97.59760,97.91556,98.14520,98.37485,98.57799,98.74580,98.87829,99.06377,
> >>>> 99.16093,99.25808,99.37290,99.45239,99.54072,99.59371,99.62904,99.66437,
> >>>> 99.69970,99.70853,99.72620,99.73503,99.77036,99.79686,99.80569,99.82335,
> >>>> 99.83219,99.84985,99.86751,99.87635,99.87635,99.90284,99.90284,99.90284,
> >>>> 99.91168,99.92051,99.92051,99.93817,99.93817,99.93817,99.95584,99.95584,
> >>>> 99.97350,99.97350,99.97350,99.97350,99.97350,99.97350,99.97350)
> >>>>
> >>>> x_value=seq(63)
> >>>>
> >>>> Thank you all in advance
> >>>>
> >>>> Dileepkumar R
> >>>>
> >>>
> >>> [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
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> >>> and provide commented, minimal, self-contained, reproducible code.
> >>>
>
> >> ______________________________________________
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> >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
>
> > ______________________________________________
> > R-help using 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 using 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.
>
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