Statistics Point estimation Concept
Maximum likelihood estimation
Builds on Likelihood functionEstimatorConsistent estimatorSample mean
Summary
Maximum likelihood estimation is a method to build estimators of unknown parameters. For observed data , the maximum likelihood estimate is a value that maximizes the likelihood function over the parameter set . In other words, it is the parameter value under which the observed data are most probable.
Remarks
The maximizer of is also the maximizer of the log-likelihood . For a smooth and an interior maximum, solves the likelihood equations . Example: for successes in Bernoulli() trials, , so . Example: for an i.i.d. sample, and . This estimator of is biased. Under regularity conditions, the estimator is consistent and asymptotically normal. Also, for a function , the maximum likelihood estimate of is .
Reading path
To understand this page from the ground up, read these 73 pages in order. The foundations come first.
- Construction of the reals from Cauchy sequences concept
- Element definition
- Integers object
- Ordered field definition
- Proposition concept
- Random experiment concept
- Rational numbers object
- Real numbers object
- Set definition
- Ring of integers statement
- Disjunction definition
- Implication definition
- Predicate definition
- Ordered pair definition
- Union definition
- Sample space definition
- The rationals form a field statement
- Existential quantifier definition
- Universal quantifier definition
- Cartesian product definition
- Subset definition
- The rationals form an ordered field statement
- Uniqueness quantifier definition
- Binary relation definition
- Universal set definition
- Order on the reals definition
- Power set definition
- Complement definition
- Function definition
- Interval definition
- Injective function definition
- Preimage of a set definition
- Sigma-algebra definition
- Countable set definition
- Event definition
- Borel sigma-algebra definition
- Probability axioms concept
- Probability measure definition
- Probability distribution definition
- Probability space definition
- Conditional probability definition
- Random variable definition
- Cumulative distribution function definition
- Discrete random variable definition
- Law of a random variable definition
- Independence of two events definition
- Convergence in probability definition
- Random variable with a density definition
- Joint probability distribution definition
- Probability mass function definition
- Mutual independence of events definition
- Expected value definition
- Identically distributed random variables definition
- Independence of two random variables definition
- Probability density function definition
- Marginal distribution definition
- Independent sigma-algebras definition
- Variance definition
- Linearity of expectation statement
- Independence of random variables definition
- Independence means the joint law is the product of the marginals statement
- Covariance definition
- Independent and identically distributed random variables definition
- Variance of a sum statement
- Expectation of a product of independent random variables statement
- Statistic definition
- Likelihood function definition
- Independent random variables are uncorrelated statement
- Estimator definition
- Variance of a sum of independent random variables statement
- Sample mean definition
- Consistent estimator definition
- Maximum likelihood estimation concept
Where this leads
15 pages build on this one.
- Poisson regression
- Consistency of the maximum likelihood estimator
- M-estimator
- Asymptotic normality of the maximum likelihood estimator
- Whittle likelihood
- Logistic regression
- Bayesian information criterion
- Akaike information criterion
- Likelihood-ratio test
- Expectation–maximization algorithm
- Wald test
- Generalized linear model
- Box–Jenkins method
- Observed information
- Point estimation
Further reading
About this page
| Tag | 0FREPFKNS7 |
|---|---|
| URI | m2://0FREPFKNS7 |
| Aliases | mle, maximum-likelihood-estimator, maximum-likelihood |
| Kind | concept |
| Writing | W1 stated |
| MSC | 62F10 |
| Uses | Likelihood function, Estimator, Consistent estimator, Sample mean |
| Same as |
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What links here
Used by
- Poisson regression
- Consistency of the maximum likelihood estimator
- M-estimator
- Asymptotic normality of the maximum likelihood estimator
- Whittle likelihood
- Logistic regression
- Bayesian information criterion
- Akaike information criterion
- Likelihood-ratio test
- Expectation–maximization algorithm
- Wald test
- Generalized linear model
- Box–Jenkins method
- Observed information
- Point estimation