CODEWITHSUNDEEP
rfunctioncurve-fittingweibull
Veronika
Veronika

Reputation: 41

Fitting Weibull function and parameter estimates

I am trying to fit a function in R to the following data:

y<-c(80.32000,  55.78819,  89.23141,  30.75780, 418.26000, 254.30000,  200,316.42667, 406.83435, 364.00304, 218.27867, 153.88019, 235.49971, 148.77052,
273.20171, 123.54065, 157.75650, 120.88961, 134.64092, 177.44000, 123.62948,87.03000,  63.22455, 132.62000, 120.95000, 129.60000, 116.32000,  60.49000,  66.59000)

x<-c(0,  0,  0,  0,  1,  1,  1,  3,  3,  3,  3,  3,  3,  7,  7,  7,  7,  7,  7, 11, 11, 11, 11, 16, 16, 16, 16, 16, 16)

I have tried several fits, but nothing really works... I guess a Weibull function would fit best. I have searched the internet to find a solution to this problem, and I have tried to adjust the code as suggested here: https://groups.google.com/g/r-help-archive/c/rym6b1K54-4?pli=1

nls(y~127*dweibull(x,shape,scale), start=c(shape=3,scale=100))

but I get the following error:

Error in numericDeriv(form[[3L]], names(ind), env) : Missing value or an infinity produced when evaluating the model. In dweibull(x, shape, scale) : NaNs were produced.

Upvotes: 0

Views: 284

Answers (1)

JJacquelin
JJacquelin

Reputation: 1705

The data is highly scatered. Moreover they are few points in the range $0<x<1$ which makes quasi impossible to sketch the shape of the function in this range. On one hand a function of Weibull kind appears convenient for $x$ large. On the other hand the kind of function convenient for small $x$ is questionable.

For example I tried the function drawn below. But with such an high scatter of the points this choice is contestable.

enter image description here

Upvotes: 1

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