How to fit data in exponential fit (R = exp(-q*D)) and find coefficient "q" using Maximum Likelihood Estimate (MLE)?

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I have data sets (D and R). I want to fit the data in terms of custom exponential fit (R = exp(-q*D)) and find the coefficient using MLE. I would be thankful if somebody can help me by writing a code.

Answers (2)

Star Strider
Star Strider on 31 Jan 2021
in the documentation for mle, see the section on pdf or cdf, dependong on what you are fitting.

Jeff Miller
Jeff Miller on 31 Jan 2021
As I read this question, it is about fitting a model rather than a distribution, so I don't think mle is appropriate. Instead, I suggest:
logR = log(R);
a = fitlm(D,logR,'intercept',false)
The resulting "Estimate" will be a least-squares estimate of q. It may or may not also be maximum likelihood, depending on your assumptions about the model errors.

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