In statistics, maximum-likelihood estimation (MLE) is a method of estimating the parameters of a statistical model.
In statistics, maximum-likelihood estimation (MLE) is a method of estimating the parameters of a statistical model.
Questions tagged [mle]
366 questions
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votes
1 answer
Use function mle2() in bbmle package(R) to get parameters for exponential and power law distribution
Here is a part of mydata:
The raw data is very big, so I upload a part of it with 20 rows.
x <- [7.6,2.2,1.1,4.7,8.6,7.5,7.5,29.9,5.0,3.0,2.4,1.5,14.9,3.9,3.7,3.2,5.0,1.7,2.9,2.3]
Here is function description
power law: y=A*x^-(u)
exponential:…
Ling Zhang
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1 answer
How can I deal with this error in the autoregressive model parameter estimation?
I am trying to use the following code for my autoregressive model parametere estimation:
ar(file[,1], aic = TRUE, order.max = NULL,method = "mle")
Then, I have the results along with the following errors:
Call:
ar(x = file[, 1], aic = TRUE,…
user3319993
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votes
1 answer
Coding likelihood and log-likelihood function in r to perform optimization
I am working on a paper that requires me to find the MLE of Gumbel’s type I
bivariate exponential distribution. I have proved the likelihood and log-likelihood functions likelihood and log-likelihood but I am struggling to implement it in r to…
Roland Fiagbe
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1 answer
Fit a Logit/Probit regression model in R using Maximum Likelihood
A simple question here:
I'd like to know if there is any function in R that can fit a logit/probit regression model using maximum likelihood method?
Currently, I'm using OLS method given by function glm (I hope it does use OLS method)... I read…
zy.G
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votes
1 answer
select k in PCA python skitlearn
I am trying to use the skitlearn package for PCA .In the documentation website given here
http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html
it is said that if n_components == ‘mle’, then mle is used to find the number…
alexander
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votes
2 answers
test cases where Maximum likelihood estimator(MLE) fails to predict the right answer
anyone knows some used case scenarios where Maximum likelihood estimator(MLE) fails to predict the right answer? with an exception of the problems which may require infinite computations, or samples or are NP-hard.
inoor
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