Hello there,
I want to perform a likelihood ratio test to check if a single exponential
or a sum of 2 exponentials provides the best fit to my data. I am new to R
programming and I am not sure if there is a direct function for doing this
and whats the best way to go about it?
#data
x <- c(1 ,10, 20, 30, 40, 50, 60, 70, 80, 90, 100)
y <- c(0.033823, 0.014779, 0.004698, 0.001584, -0.002017, -0.003436,
-0.000006, -0.004626, -0.004626, -0.004626, -0.004626)
data <- data.frame(x,y)
Specifically, I would like to test if the model1 or model2 provides the best
fit to the data-
model 1: y = a*exp(-m*x) + c
model 2: y = a*exp(-(m1+m2)*x) + c
Likelihood ratio test = L(data| model1)/ L(data | model2)
Any help would be most appreciated. Thanks in advance.
Diviya
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