[R] almost logistic data evaluation

PIKAL Petr
Tue, 09 Jun 2020 12:29:27 -0000

Hallo Patrick



Thanks. Actually ?y? is growing temperature, which, at some point, rise more
rapidly due to exothermic reaction. This reaction starts and ends and proceed
with some speed (hopefully different in each material). I hope to get starting
point and speed of temperature rise by evaluating shape of curves.



I do not think left censoring could help. As seen from data plot at first ?y? is
linearly growing but logistics curve needs to start from flat (left asymptote)
and end as flat (right asymptote, AFAIK). With linear growth on left site simple
logistics fail to model data correctly.



One option could be to estimate linear part and deduct it from the data and fit
simple logistics model on deducted data. If this is the only way, I will do it
but I, as always, first try to ask helpful and ingenious people on this list.



Cheers

Petr



From: Patrick (Malone Quantitative) <malone at malonequantitative.com>
Sent: Tuesday, June 9, 2020 2:05 PM
To: PIKAL Petr <petr.pikal at precheza.cz>
Subject: Re: [R] almost logistic data evaluation



Off-list because off-topic.



I didn't plot your data, but took your word that "They resemble
logistics curve but they do not start as flat curve but
growing curve."



You also didn't say what your research question is. But if you're trying
to model the growth, could it be *part* of a logistic curve, with a censoring
point on the left? Maybe that helps with some avenues.



On Tue, Jun 9, 2020 at 7:21 AM PIKAL Petr <petr.pikal at precheza.cz
<mailto:petr.pikal at precheza.cz> > wrote:

Dear all

I have several files with data like those.

> dput(temp)
temp <- structure(list(V1 = c(0L, 15L, 30L, 45L, 60L, 75L, 90L, 105L,
120L, 135L, 150L, 165L, 180L, 195L, 210L, 225L, 240L, 255L, 270L,
285L, 300L, 315L, 330L, 345L, 360L), V2 = c(98.68666667, 100.8,
103.28, 107.44, 110.06, 114.26, 117.6, 121.04, 123.8533333, 126.66,
129.98, 134.1866667, 139.04, 144.6, 152.08, 161.3, 169.8733333,
176.6133333, 181.92, 186.0266667, 188.7533333, 190.7066667, 192.0533333,
192.9933333, 193.3533333)), class = "data.frame", row.names = c(NA,
-25L))

plot(temp)

They resemble logistics curve but they do not start as flat curve but
growing curve. Can you please give me some hints how to deal with such data?
I know that it is not strictly speaking R question but maybe somebody could
give me directions how to model such data and find model parameters.

I considered stepwise regression but it is not completely satisfactory.

Thanks beforehand
Petr Pikal
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