I tried to find it with MLE method by R Program. The syntax as follows:
llomax=function(alpha,theta){
n=length(dataklaim)
x=dataklaim
-n*log(alpha)-alpha*n*log(theta)+(alpha+1)*sum(log(x+theta))}#-loglikelihood
library(stats4)
estlomax=mle(minuslog=llomax,start=list(alpha=80.805,theta=5.70E+07))
summary(estlomax)
Actually, I would like to find alpha parameter and theta parameter. But the sntax need initial value, which I enter the values alpha=80.805,theta=5.70E+07 who I get them from Easy Fit. Are there procedures to find these parameters in R programming?
But, if there is a procedure by MATLAB, I will accept it also. I attach the file to understand my question bettter.
So presumably you have some data and you think it follows the lomax distribution, but you need to find the parameters that fit the distribution to the data?
It's not immediately clear, but the usual Bayesian way of doing this is use the log-likelihood function you attached in the pdf, so you select initial parameters, then you calculate the log-likelihood and this tells you how good your parameters fit your data. By changing the parameters, you change the log-likelihood, so all you need to do is use the log-likelihood as a fitness or gradient in some optimisation technique in matlab.
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