[Rd] infelicity with axTicks

Spencer Graves @pencer@gr@ve@ @end|ng |rom prod@y@e@com
Sun Jun 22 18:43:02 CEST 2025



On 6/22/25 10:13, Duncan Murdoch wrote:
> On 2025-06-22 8:15 a.m., Spencer Graves wrote:
>> If the range fed to axTicks is too narrow, the output is only 2 points;
>> shouldn't it degenerate to using "pretty" in such cases?
>>
>>
>> EXAMPLE:
>>
>>
>> ylims2 <- c(0.2, 0.8)
>> get_axp <- function(x) 10^c(ceiling(x[1]), floor(x[2]))
>> ## mimic par("yaxs") == "i"
>> usr.i2 <- log10(ylims2)
>> (aT.i2 <- axTicks(side = 2, usr = usr.i2,
>>         axp = c(get_axp(usr.i2), n = 3), log = TRUE, nintLog = 5))
>> #[1] 0.2 0.5
> 
> I don't understand your point.  If I do
> 
>    plot(ylims2, ylims2, log="xy", yaxs="i", xaxs="r")
> 
> then both axes get ticks at the pretty(ylims2) locations.  If I set yaxp 
> or xaxp to the  values you used, then I get c(0.2, 0.5), but why would I 
> do that?


I want to plot one set of points and lines with 3 axes for both : for 
the cumulative hazard (H), the survival probability [S = exp(-H)], and 
the probability of failure (1-S).


I'm programming around it. This may be too rare an application to bother 
with.


Thanks for the reply. Spencer Graves


p.s. My specific application is my claim that the hazard rate for a 
nuclear war in the next year increases with the time since the last 
detonation in anger, namely Nagasaki 1945-08-09, for two reasons: (1) 
Nuclear proliferation and (2) managers of complex systems subject to 
rare but catastrophic failures "learn" from experience that they can 
"safely" take ever greater risks -- until a catastrophe proves them 
wrong. I estimate a range of subjective probabilities that each of 13 
major "nuclear close calls" like the 1962 Cuban missile crisis might 
have actually ended in a nuclear war, converted each range into a range 
for the cumulative hazard for each incident, then summed imputed means 
and variances for the computed hazard to get a total cum hazard. Then I 
converted that to the estimate of the Weibull scale parameter assuming 
the shape parameter is 1, 1.5, or 2:


https://docs.google.com/spreadsheets/d/18Iutk8BqmiBND06xbjCIP6DmxMKAliyxO9g88sL5e2Y/edit?usp=sharing


After I get my plot, I plan to post a description of this to Wikiveristy 
and then circulate that to leading experts and potential collaborators 
in getting something on this published.

> 
> Duncan Murdoch
>



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