Maximum Likelihood is a method by which parameters of a statistical model can be calculated, in such a way as to maximise the likelihood that the observed data could have occurred. Contrast with Method of Moments.
Phylogenetic method that gives an estimation of the likelihood of a particular tree given a certain model of nucleotide substitution. Advantage is that it is based on a specific model of sequence evolution; gives a probability at each internode; and, the complete nucleotide sequnce is used. Disadvantage is that this method takes a long time to compute (relative to other methods).
A statistical method of estimation.
A method of determining which of two or more competing hypotheses (such as alternative phylogenetic trees) yields best fits to the data.
( ML) This is a method of inferring phylogenetic relationships using a pre-specified (often user-specified) model of sequence evolution. Given a tree (a particular topology, with branch lengths), the ML process asks the question "What is the likelihood that this tree would have given rise to the observed datamatrix, given the pre-specified model of sequence evolution?"
An approach to tree construction that begins with the possible trees and deduces which one is most likely given the data and an explicit model of evolution.
One of several criteria that may be optimised in building phylogenetic trees from molecular sequence data. The optimal tree is the one that maximises the statistical likelihood that the specified evolutionary model produced the observed character-state data; the models specify the probabilities of character-state changes through evolutionary time (cf. distance, parsimony).
Statistical method for estimating a population parameter most likely to have produced the sample observations.
Another training or estimation method. The maximum likelihood estimate of a parameter is the value of a parameter that maximizes the probability that the data came from the population defined by the parameter.
Maximum likelihood estimation (MLE) is a popular statistical method used to make inferences about parameters of the underlying probability distribution from a given data set. It has widespread applications in various fields. These include econometrics and hypothesis testing in medical research.