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
17
votes
3 answers

MLE error in R: initial value in 'vmmin' is not finite

Suppose I have 2 data.frame objects: df1 <- data.frame(x = 1:100) df1$y <- 20 + 0.3 * df1$x + rnorm(100) df2 <- data.frame(x = 1:200000) df2$y <- 20 + 0.3 * df2$x + rnorm(200000) I want to do MLE. With df1 everything is ok: LL1 <- function(a, b,…
BiXiC
  • 933
  • 3
  • 9
  • 29
7
votes
1 answer

Estimating the parameters of a custom distribution using mle()

I have the following code that I wish to estimate the parameters of a custom distribution. For more details on the distribution. Then using the estimated parameters I want to see if the estimated PDF resembles the distribution of the given the data…
nashynash
  • 375
  • 2
  • 19
7
votes
1 answer

R: trouble with mle() error: non-finite finite-difference value [2]

I have a simple x, y data.frame. mydata <- data.frame(days = 1:96, risk = c(5e-09, 5e-09, 5e-09, 1e-08, 4e-08, 6e-08, 9e-08, 1.5e-07, 4.2e-07, 7.2e-07, 1.02e-06, 1.32e-06, 1.66e-06, 2.19e-06, 2.76e-06,…
Adrian
  • 9,229
  • 24
  • 74
  • 132
7
votes
0 answers

Maximum Likelihood Estimation for Multivariate Normal Distribution in Python

I am trying to fit the parameters of a multivariate normal distribution using MLE. import numpy as np from scipy.stats import norm from scipy.optimize import minimize from scipy.stats import multivariate_normal as mnorm def…
iwbabn
  • 1,275
  • 4
  • 17
  • 32
6
votes
2 answers

Why ImportError: cannot import name 'AutoReg' from 'statsmodels.tsa.ar_model' occuring?

I am trying to do MLE regression using AR(p) by importing the module from statsmodels.tsa.ar_model import AutoReg, ar_select_order, but this ImportError keeps coming. How to solve this? Is there any other way I can do Autoregression in Python?
Asad Tan
  • 79
  • 1
  • 1
  • 7
6
votes
1 answer

Weibull Parameter estimation using Apache Commons Math

I need to estimate the shape and scale parameters of a Weibull distribution from a sample data using MLE. I checked the WeibullDistribution class of Apache commons Math but it doesn't have such functionality. Any suggestion? I need to use the class…
Tesse M
  • 101
  • 1
  • 5
6
votes
1 answer

Numerical Method for SARIMAX Model using R

My friend is currently working on his assignment about estimation of parameter of a time series model, SARIMAX (Seasonal ARIMA Exogenous), with Maximum Likelihood Estimation (MLE) method. The data used by him is about the monthly rainfall from 2000…
crhburn
  • 103
  • 1
  • 8
6
votes
2 answers

Calculation of return levels based on a GPD in different R packages

I am performing an extreme value analysis for meteorological data, to be precise for precipitation data available in mm/d. I am using a threshold excess approach for estimating the parameters of a generalized Pareto distribution with a maximum…
Homunculus
  • 91
  • 1
  • 8
5
votes
1 answer

How to incorporate weights into a likelihood function?

I want to incorporate weights into the likelihood to do what the svyglm does with weights. According to Jeremy Miles and elsewhere, svyglm function uses weights to "weight the importance of each case to make them representative (to each other,…
Krantz
  • 1,424
  • 1
  • 12
  • 31
5
votes
1 answer

Hessian Matrix in Maximum Likelihood - Gauss vs. R

I am struggling with the following problem. In a nutshell: Two different software packages (Gauss by Aptech and R) yield totally different Hessian Matrices in a Maximum Liklihood Procedure. I am using the same procedure (BFGS), the exact same data,…
timsad
  • 51
  • 2
5
votes
1 answer

Python package :MLE for Dirichlet distribution

I was wondering if someone knew about a python package that implements MLE to estimate parameters of a Dirichlet distribution.
cryp
  • 2,285
  • 3
  • 26
  • 33
4
votes
0 answers

"optim" function fails to converge for maximum likelihood estimation in a random-effect model

I have a longitudinal dataset for plant growth that includes repeated measurements in different seasons. I am trying to estimate the parameters for a growth equation using this dataset. The growth equation is as follows: Lt = 150*((1 +…
TKH_9
  • 105
  • 1
  • 7
4
votes
1 answer

bnlearn::bn.fit difference and calculation of methods "mle" and "bayes"

I try to understand the differences between the two methods bayes and mle in the bn.fit function of the package bnlearn. I know about the debate between the frequentist and the bayesian approach on understanding probabilities. On a theoretical level…
locom
  • 115
  • 9
4
votes
1 answer

maximum likelihood in double poisson distribution

First I am using "rmutil" package to make simulation of double poisson distributed data. The difference of poisson and double poisson is that, double poisson allows overdispersion and underdispersion where mean and variance not necessary equal. This…
Miyazaki
  • 99
  • 8
4
votes
2 answers

sklearn PCA with n_components = 'mle' and svd_solver = 'full' results in math domain error

My Question is highly related to math domain error while using PCA I get the following error: File "$path$\Python\Python36\lib\site-packages\sklearn\decomposition\pca.py", line 88, in _assess_dimension_(1. / spectrum_[j] - 1. / spectrum_[i])) +…
Yannic Bürgmann
  • 6,301
  • 5
  • 43
  • 77
1
2 3
…
24 25