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

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.

Answer 1

[Star Strider]

in the documentation for mle, see the section on pdf or cdf, dependong on what you are fitting.

Answer 2

[Jeff Miller]

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.