I searched on the internet but I could not find any clues about my question. Can anyone just simply tell what is the difference between restricted and unrestricted parameter space in MLE?

I have used bimodalitytest package in R, the function bimodality.test which performs the likelihood ratio test for bimodality.

It's description is:

"This function performs the likelihood ratio test for a given dataset. It tests the null hypothesis, whether a two components normal mixture is bimodal. Therefore it calculates the maximum likelihood estimators for the restricted and non restricted parameter space and returns for example the likelihoodratio and the p-value."

(just for learning purposes)

I searched on the internet but I could not find any clues about my question. Can anyone just simply tell what is the difference between restricted and unrestricted parameter space in MLE?

I have used bimodalitytest package in R, the function bimodality.test which performs the likelihood ratio test for bimodality.

It's description is:

"This function performs the likelihood ratio test for a given dataset. It tests the null hypothesis, whether a two components normal mixture is bimodal. Therefore it calculates the maximum likelihood estimators for the restricted and non restricted parameter space and returns for example the likelihoodratio and the p-value."

And I know the next question depends on the purpose of research and other points, but let me also ask it:

Which one do you suggest for MLE? restricted or non restricted parameter space? On which basis should I decide on using them?

I searched on the internet but I could not find any clues about my question. Can anyone just simply tell what is the difference between restricted and unrestricted distribution parameter estimation?

(just for learning purposes)

I searched on the internet but I could not find any clues about my question. Can anyone just simply tell what is the difference between restricted and unrestricted parameter space in MLE?

I have used bimodalitytest package in R, the function bimodality.test which performs the likelihood ratio test for bimodality.

It's description is:

"This function performs the likelihood ratio test for a given dataset. It tests the null hypothesis, whether a two components normal mixture is bimodal. Therefore it calculates the maximum likelihood estimators for the restricted and non restricted parameter space and returns for example the likelihoodratio and the p-value."

(just for learning purposes)