Fit data to exponential model in R

Question:

Goodnight,

I have two variables about growth in insects: y- measurements of head width(0.5,0.8,0.10.0.12,0.16) x- age at which they were measured (1,2,3,4,5)

I need to see if this growth fits with exponential growth. I need the values ​​of the generated equation, p and r^2, in addition to F (although F don't think that's possible, eh?).

I didn't find how to do this in R.

Thanks

Bruna

Answer:

Your question lacks some explanations, but in a basic way you can do this in R:

x<- c(1,2,3,4,5)
y<- c(0.5,0.8,0.10,0.12,0.16)

cbind(x,y)
n<-length(x)

cbind(x,log(y),x*log(y),x^2)
cbind(sum(x),sum(log(y)),sum(x*log(y)),sum(x^2))
num = sum(x*log(y)) - sum(x)*sum(log(y))/n
denom = sum(x^2) - sum(x)^2/n
a=num/denom
b=sum(log(y))/n - a*sum(x)/n

A = exp(a)
B = exp(b)

plot(x,y,col="blue",pch=19)
curvaexp<-curve(B*exp(a*x), NULL,NULL, 5, add=T, col=2)

curvaexp

r2.lm = lm(y ~ curvaexp$y) 
r2<- summary(r2.lm)$r.squared #<--- Coeficiente de Determinaçao
var.test(y, curvaexp$y)# variancia F
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