Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)
Probability Models, Detection, and ML + MMSE estimation
Code for reproducing the MLE examples in the manuscript "A Cornucopia of Maximum Likelihood Algorithms" by Lange, Li, and Zhou
Jie Shao He Ju Li (Zheng Tai Fen Bu , Bo Song Fen Bu , Jia Ma Fen Bu )Zhan Shi Liao Ji Da Si Ran Gu Ji . This paper introduces and gives examples (normal distribution, Poisson distribution, gamma distribution) to show the MLE.
Maximum likelihood fits for low photon count data - For active develeopment visit gitlab.peulen.xyz
UW course projects
Aspects of numerical analysis in the field of data science (matrix inversion, splines, function optimization, bayesian statistics, MCMC, etc)
MLE estimation, Linear Regression, Linear Bayesian Regression, Naive Bayes
Machine Learning for Data 3141 Reichman University Spring 2022 - 6 Homework Projects
Statistical estimation of optimal solutions for combinatorial optimization problems
L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions
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)
For master's students in mathematical economics, focusing on econometric methods and applications.
Implementation of unigram/bigram language models, noisy channel and pointwise mutual information for natural language processing.
This is a repository with the assignments of IE675b Machine Learning course at University of Mannheim.
A natural time analysis of the Earthquake Cycles in Taiwan by evaluating EPS scores using R and Python.
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.
Ancestry Calculator for WeGene, It features population admixture model and MLE (Maximum Likelihood Estimation) algorithm to estimate admixture.
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