In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed...

Maximum likelihood sequence estimation (MLSE) is a mathematical algorithm that extracts useful data from a noisy data stream. For an optimized detector...

the quantity one wants to estimate. MAP estimation is therefore a regularization of maximum likelihood estimation, so is not a well-defined statistic of...

enhancement or noise correlation, the PRML sequence detector performs maximum-likelihood sequence estimation. As the operating point moves to higher linear...

function solely of the model parameters. In maximum likelihood estimation, the argument that maximizes the likelihood function serves as a point estimate for...

No. 5, pp.3666-3668 Sept. 1987 D. Forney, "Maximum Likelihood Sequence Estimation of Digital Sequences in the Presence of Intersymbol Interference"...

variation distance to a multivariate normal distribution centered at the maximum likelihood estimator θ ^ n {\displaystyle {\widehat {\theta }}_{n}} with covariance...

parameters of a logistic regression are most commonly estimated by maximum-likelihood estimation (MLE). This does not have a closed-form expression, unlike linear...

Principle of maximum entropy Maximum entropy probability distribution Maximum entropy spectral estimation Maximum likelihood Maximum likelihood sequence estimation...

efficiently. The maximum subarray problem was proposed by Ulf Grenander in 1977 as a simplified model for maximum likelihood estimation of patterns in digitized...

Logistic regression Conditional entropy Kullback–Leibler distance Maximum-likelihood estimation Mutual information Perplexity Thomas M. Cover, Joy A. Thomas...

optimum point estimate of the parameter(s)—e.g., by maximum likelihood or maximum a posteriori estimation (MAP)—and then plugging this estimate into the formula...

0 {\displaystyle t=t_{0}} . Estimation of the parameters in an HMM can be performed using maximum likelihood estimation. For linear chain HMMs, the Baum–Welch...

of formulating an estimator within Bayesian statistics is maximum a posteriori estimation. Suppose an unknown parameter θ {\displaystyle \theta } is...

expectation–maximization (EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models...

cannot be large. Kaplan–Meier estimator can be derived from maximum likelihood estimation of the discrete hazard function. More specifically given d i...

taxa. Maximum parsimony is used with most kinds of phylogenetic data; until recently, it was the only widely used character-based tree estimation method...

2023-09-06. Yang, Ziheng (September 1994). "Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: Approximate...

likelihood function is the value which is most strongly supported by the evidence. This is the basis for the widely used method of maximum likelihood...

consequences: the maximum likelihood estimates (MLE) of the parameters will usually be biased, as well as inconsistent (unless the likelihood function is modified...

statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density (also known as the...

owner and operator of several Toronto-based sports teams Maximum likelihood sequence estimation, an algorithm This disambiguation page lists articles associated...

optimal evolutionary ancestry between a set of genes, species, or taxa. Maximum likelihood, parsimony, Bayesian, and minimum evolution are typical optimality...

In the statistical theory of estimation, the German tank problem consists of estimating the maximum of a discrete uniform distribution from sampling without...

performed by applying a maximum likelihood test to a given tree topology and sequence alignment. This produces two log-likelihood values, one with the clock...

estimation". Studies on: Filtering, optimal control, and maximum likelihood estimation. Convention DRET no. 89.34.553.00.470.75.01. Research report no...

doi:10.1016/S0165-4896(02)00023-9. Manski, Charles F. (1975). "Maximum Score Estimation of the Stochastic Utility Model of Choice". Journal of Econometrics...

probabilities given by that histogram. The histogram is itself a maximum-likelihood (ML) estimate of the discretized frequency distribution [citation...

Discs from 25 GB to 33.4 GB via a technology called i-MLSE (maximum likelihood sequence estimation). The higher-capacity discs, according to Sony, would be...

the likelihood of phylogenetic trees using multiple sequence alignment data. Thus, substitution models are central to maximum likelihood estimation of...