Stack Overflow
Stack Overflow

Questions tagged [mle]

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.

366 questions
3
votes
0 answers

Python ARMA MLE (Implementing Algorithms from Literature)

Overview I am trying to implement autoregressive moving average (ARMA) parameter optimization using maximum likelihood estimation (MLE) via the Kalman Filter. I know that I can fit ARMA models using the statsmodels package in Python, but I want to…
Nick Settje
  • 3,022
  • 1
  • 11
  • 18
3
votes
2 answers

Maximum Likelihood Estimation for three-parameter Weibull distribution in r

I want to estimate the scale, shape and threshold parameters of a 3p Weibull distribution. What I've done so far is the following: Refering to this post, Fitting a 3 parameter Weibull distribution in R I've used the functions EPS =…
Tim-TU
  • 408
  • 1
  • 4
  • 13
3
votes
1 answer

Power law fitted by `fitdistr()` function in package `fitdistrplus`

I generate some random variables using rplcon() function in package poweRlaw data <- rplcon(1000,10,2) Now, I want to know which known distributions fit the data best. Lognorm? exp? gamma? power law? power law with exponential cutoff? So I use…
Ling Zhang
  • 281
  • 1
  • 3
  • 13
3
votes
0 answers

Initial guess for Newton-Raphson iteration method in Maximum Likelihood Estimation

I want to estimate the four parameters of Exponentiated Modified Weibull Extension (EMWE) distribution introduced by Sarhan and Apaloo (2013) with the Maximum Likelihood Estimation (MLE). This distribution is used in reliability and survival…
crhburn
  • 103
  • 1
  • 8
3
votes
0 answers

clustered (grouped) standard errors Maximum Likelihood R

I'm doing the following maximum likelihood estimation using mle2 function from bbmle package: llik.probit2<- function(aL,beta, Ks, Kw, Bs, Bw, dta){ Y <- as.matrix(dta$qualified) sce1 <- as.matrix(dta$eds) wce1 <- as.matrix(dta$edw) sce1_obs…
Nidjsi
  • 73
  • 1
  • 5
3
votes
0 answers

How to extract the value of MLE in r using mle function

My probability distribution function is f(x;r)=(1+r)/Γ(1/(1+r))exp(-x^(1+r)) , 0-1 I am using following code: library(stats4) x3=c(0.927869895,0.000559193,0.059761785,0.361542986,0.274291999,0.563373589, …
aorstat
  • 31
  • 4
3
votes
1 answer

understanding R's mle2 function and its parameters

I apologize if this question is dumb as all get out. I want to leverage R's mle2() function to find optimum parameters to a particular statistical function; I presume it does so using gradient descent? So I've got my call like this: r =…
user2415010
2
votes
1 answer

How to maximize joint likelihood function with different (but fixed) means

The goal Optimize a common dispersion parameter across groups of data over fixed mu, where mu changes by group. The problem I have n=10 groups of data, each of which I assume is a random sample from a negative binomial distribution with fixed…
cmcrowley
  • 95
  • 6
2
votes
1 answer

Adding a static element across slider steps in a R plotly graph

I am giving a tutorial on MLE and am trying to figure out how to add a static grouping of points to a plotly graph. Obviously the idea is that as I slide the normal distributions over you can see that the points correspond to a lower or higher…
brzig
  • 23
  • 4
2
votes
0 answers

Maximum likelihood estimator stuck at bounds

I'm working on setting up a maximum likelihood estimator to estimate the parameters for a dirichlet-multinomial distribution. Based on what I've seen elsewhere, it looks like the function ddirichlet.multinom() is working as expected, but when I pass…
Mark Rieke
  • 306
  • 3
  • 13
2
votes
1 answer

Maximum Likelihood in R for a log function

I am having some issues on using the mle function in R. The model I have is, log(Y)~log(K)+log(L), and when I input this model into R using I keep on getting error message about missing the function minuslog1. How do I resolve this issue using the…
Warhawk1987
  • 307
  • 1
  • 9
2
votes
3 answers

MLE application with gekko in python

I want to implement MLE (Maximum likelihood estimation) with gekko package in python. Suppose that we have a DataFrame that contains two columns: ['Loss', 'Target'] and it length is equal to 500. First we have to import packages that we need: from…
Shayan
  • 5,165
  • 4
  • 16
  • 45
2
votes
1 answer

R: error on estimating mle with MaxLik() package

My purpose is to find maximum likelihood estimator using Newton Raphson algorithm and compare the solution with glm(). so I tried to use maxLik() in R. And it turns out error, I have not use this package before, please fix this error, thank you!! d…
Jasmine Helen
  • 99
  • 8
2
votes
0 answers

How to repeat generating random sample 1000 times without for loop and draw the plots of alpha estimators?

I have to generate one random sample with n= 20, from beta distribution(alpha=5,beta=1) and calculate MLE for alpha. I did this using the function rbeta and ebeta: alfa = 5 beta=1 n = 20 sample<- rbeta(n,alfa,beta) mle_alfa <- ebeta(proba, method =…
user13696679
  • 65
  • 5
2
votes
1 answer

Simulation test for Bernoulli trials for increasing sample size in R

In R software, I am trying to generate a simulation plot for bernoulli trial for different sample sizes as below I have generated the proportions for given sample size and repeated the process 1000 times. But I dont understand, how to plot the…
Bilal Para
  • 65
  • 1
  • 8
1 2
3
…
24 25