This smells like homework, which the Posting Guide indicates is off topic.
I am not aware of "the function" that will solve this, but if you know what a
gradient is analytically then you should be able to put together a solution
very similar to the code you already have with the addition of using the coef
function.
--
Sent from my phone. Please excuse my brevity.
On April 5, 2018 3:44:03 AM PDT, g l <gnuli...@gmx.com> wrote:
>Readers,
>
>Data set:
>
>t,c
>0,100
>40,78
>80,59
>120,38
>160,25
>200,21
>240,16
>280,12
>320,10
>360,9
>400,7
>
>graphdata<-read.csv('~/tmp/data.csv')
>graphmodeld<-lm(log(graphdata[,2])~graphdata[,1])
>graphmodelp<-exp(predict(graphmodeld))
>plot(graphdata[,2]~graphdata[,1])
>lines(graphdata[,1],graphmodelp)
>
>Please what is the function and syntax to obtain gradient values for
>the model curve at various requested values, e.g.:
>
>when graphdata[,1] at values = 100, 250, 350 ?
>
>______________________________________________
>R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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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@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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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.
