Likelihood

This contribution is made in order to calculate the maximum likelihood contour plots of any function. Just replace the file with your function change some basic settings in the file and there you go. The objective function has to return a scalar. There are two settings only: the range of the... Platforms: Matlab

Several functions for evaluating the exact negative log-likelihood of ARMA models in O(n) time using the Kalman Filter. Platforms: Matlab

PoissonMax is a handy, small, command prompt based application specially designed to compute Poisson maximum likelihood mean frequency from limiting dilution data, with 95% confidence limits and Chi-square value. Platforms: Windows

Many image problems require some kind of detection of objects, in which there is a natural variation in appearance of the objects between the images.Using a basic PCA classifier, this script is able to execute two type of actions: pattern recongitions and change detections.It has various... Platforms: Windows, Mac, *nix, Matlab, BSD Solaris

It applies to the cases when likelihood function is explicit Platforms: Matlab

Two files:They find the Maximum Likelihood Estimators for the parameters of the Gumbel distribution for the minimum and the Gumbel distribution for the maximum. Platforms: Matlab

(p)IPHULA is a software that investigates parameters of population history based on a Monte Carlo simulation using the maximum likelihood framework. Further details on how to compile, install, run, and use this program can be found in the (p)IPHULA manual (PDF). Reference: The method is... Platforms: Mac

Frappe is a program for determining the likelihood of any given number of successes in the open source rpg Fringe (http://www.box.net/shared/v38ckzapbj). Platforms: Windows, Mac, Linux

Phight - a phylogeny tree building program Currently, it supports Likelihood method and distance method. This program will includes diagnostic function as a special feature. Platforms: Windows, Mac, Linux

A maximum likelihood fitting package based on ROOT/RooFit for HEP. The fitting is driven by a text file and includes the following main options: 1) fitting, plotting and extraction of PDFs; 2) fitting of maximum likelihood models; 3) creation of projection and sPlot plots; 4) scanning about... Platforms: Mac

The Expectation-Maximization algorithm (EM) is widely used to find the parameters of a mixture of Gaussian probability density functions (pdfs) or briefly Gaussian components that fits the sample measurement vectors in maximum likelihood sense [1]. In our work, the expectation-maximization (EM)... Platforms: Matlab

How to fit a 2D Gaussian function to noisy data in Matlab? Or data with another number of dimensions and arbitrary fit function?It took me a while to find out how Matlab does this by the functions lsqcurvefit, fmincon or fminsearch. This project demonstrates how to use these functions to fit ND... Platforms: Matlab

This function calculate the performance, based on Bayes theorem, of a clinical test. The input is based on a 2x2 matrix (true positive, false positives; false negative, true negatives).The Outputs are:- Prevalence of disease- Test Sensibility with 95% confidence interval- Test Specificity with... Platforms: Matlab

This Matlab/C code contains routines to perform level set image segmentation according to:(1) various multiphase (multiregion) formulations, including a fast scheme where the computation load grows linearly with the number of regions and,(2) various region-based image descriptions which... Platforms: Matlab

Functions written in 2007 for Master Thesis: "Simulating dependent random variables using copulas. Applications to Finance and Insurance". Functions include MVCOPRND - multivariate copula generator, CMLSTAT for estimation of copula parameters using Canonical Maximum Likelihood Method. Functions... Platforms: Matlab

this function use the maximum log likelihood algorithm For Detection of onset of change It assume an inhomogeneous Poisson process that has a constant intensity ?0 until the change point, and a constant intensity ?1 thereafter. (step function where ?0 and ?1 are unknown) A is a random variable... Platforms: Matlab

A stack-based sequential depth-first decoder that returns Maximum-Likelihood solutions to spherical LAST coded MIMO system-type problems, i.e., a lattice decoder with spherical boundary control. In such problems, the depth of the search tree is known but the number of children per node is not... Platforms: Matlab

Bayesian Model Averaging for linear models under Zellner's g prior. Options include: fixed (BRIC, UIP, ...) and flexible g priors (Empirical Bayes, hyper-g), 5 kinds of model prior concepts, and model sampling via model enumeration or MCMC samplers (Metropolis-Hastings plain or reversible jump).... Platforms: Matlab

A stack-based sequential priority first decoder that returns Maximum-Likelihood solutions to spherical LAST coded MIMO system-type problems, i.e., a lattice decoder with spherical boundary control. In such problems, the depth of the search tree is known but the number of children per node is not... Platforms: Matlab

Choose automatically the number of bin of a regular histogram using penalized likelihood procedure following paper of BirgdoTe-Rozenholc in ESAIM P&S (2006), 10, pp.24-45 "How many bins should be put in a regular histogram?" Platforms: Matlab