In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed... 66 KB (9,609 words) - 17:40, 12 April 2024 |
quantity one wants to estimate. MAP estimation can therefore be seen as a regularization of maximum likelihood estimation. Assume that we want to estimate... 10 KB (1,639 words) - 21:28, 21 April 2024 |
actual parameter. In maximum likelihood estimation, the arg max (over the parameter θ {\displaystyle \theta } ) of the likelihood function serves as a... 62 KB (8,542 words) - 05:19, 22 April 2024 |
reduced) maximum likelihood (REML) approach is a particular form of maximum likelihood estimation that does not base estimates on a maximum likelihood fit... 4 KB (455 words) - 18:50, 2 December 2023 |
Maximum likelihood sequence estimation (MLSE) is a mathematical algorithm to extract useful data out of a noisy data stream. For an optimized detector... 5 KB (603 words) - 19:36, 27 October 2022 |
modeled; see § Maximum entropy. The parameters of a logistic regression are most commonly estimated by maximum-likelihood estimation (MLE). This does... 127 KB (20,600 words) - 21:36, 27 April 2024 |
M-estimator (redirect from M-estimation) function is a sample average. Both non-linear least squares and maximum likelihood estimation are special cases of M-estimators. The definition of M-estimators... 22 KB (2,845 words) - 05:29, 1 January 2024 |
In statistics a quasi-maximum likelihood estimate (QMLE), also known as a pseudo-likelihood estimate or a composite likelihood estimate, is an estimate... 4 KB (420 words) - 01:35, 21 January 2023 |
Linear regression (category Estimation theory) present). It is equivalent to maximum likelihood estimation under a Laplace distribution model for ε. Adaptive estimation. If we assume that error terms... 69 KB (9,516 words) - 01:35, 28 April 2024 |