Code for reproducing the MLE examples in the manuscript “A Cornucopia of Maximum Likelihood Algorithms“ by Lange, Li, and Zhou
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Updated
Sep 8, 2024 - Julia
Code for reproducing the MLE examples in the manuscript “A Cornucopia of Maximum Likelihood Algorithms“ by Lange, Li, and Zhou
L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions
Maximum likelihood fits for low photon count data - For active develeopment visit gitlab.peulen.xyz
Numerical MLE solvers
Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)
Assignments completed for my Machine Learning course: Topics include probability and statistics proofs, MLE/MAP parameter estimation, EM Algorithm, Bayes Theorem implementations, gradient descent methods, Neural Networks and Deep Learning.
Machine Learning for Data 3141 Reichman University Spring 2022 - 6 Homework Projects
翻新的最大似然估计框架 copied and renewed maximum likelihood estimation package
This is a paper dealing with truncation and censored data in the insurance agency. We go over Maximum Likelihood Estimation and the EM Algorithm for censored exponential data.
Here for a small dataset we have used OLS(Ordiniary Least Square) and MLE(Maximum likelihood Estimation ) to calculate the regression parameters slope(b1),intercept(b0) and standard deviation of reisduals.At the end we can conclude that both the methods of estimation produces the same result.
The maximum likelihoood estimator approach is used here for calculating the Regression parameter that is slope(b1),intercept(b0) and standard deviation of error/residuals. Then Result or the output for the regression parameters using the OLS(ordiniary Least Sqaure) estimation method versus the MLE(MAximum Likelihood Estimation) method is compare…
Some deep learning assignment questions, solutions and codes
Material for Lab 12 for the course
Java based implementation of an MLE method using chi square test to calculate interference during meiotic crossover (the number of double strand dna breaks that don't result in a crossover)
Classification task of body positions of skeletal body movements recorded from a Kinect device (Kinect Gesture Dataset). A Bayesian approach is employed using a Linear Gaussian Model and Maximum Likelihood Estimation, assuming dependencies between skeleton joints.
A natural time analysis of the Earthquake Cycles in Taiwan by evaluating EPS scores using R and Python.
介绍和举例(正态分布、泊松分布、伽马分布)展示了极大似然估计。This paper introduces and gives examples (normal distribution, Poisson distribution, gamma distribution) to show the MLE.
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