I can't figure out how to reconstruct the results nor the formula from the predict
function of a linear model. I get the same results also when using this data in ggplot geom_smooth(method='lm',formula,y ~ exp(x)).
Here's some sample data
x=c(1,10,100,1000,10000,100000,1000000,3000000)
y=c(1,1,10,15,20,30,40,60)
I would like to use an exponential function so (ignore for the moment that I log the x value, because exp() fails for very large values):
model = lm( y ~ exp(log10(x)))
mypred = predict(model)
plot(log(x),mypred)
I have tried
lm_coef <- coef(model)
plot(log10(x),lm_coef[1]*exp(-lm_coef[2]*x))
However this is giving me a decreasing exponential instead of the increasing. My goal is to extract the equation of the exponential function so I can reuse the coefficients in another context.. What equation is predict() using and is there a way to see it?
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