Probability theory and stochastic processes Expectation, moments and transforms Concept
Moment
Summary
The moments of a random variable are the expected values of its powers. The first moment is the mean. The node moment gives the precise definition for random variables.
Where this leads
18 pages build on this one.
- Log-normal distribution
- Pareto distribution
- Indeterminate moment problem
- Positivity of Hankel matrices of moments
- Moment problem
- Moments and orthogonal polynomials
- Hausdorff moment problem
- Berry–Esseen theorem
- Determinate moment problem
- Cumulant
- Moments of the log-normal distribution
- Krein's condition
- Vanishing moments of a wavelet
- Carleman's condition
- Hamburger moment problem
- Stieltjes moment problem
- Chebyshev–Markov–Stieltjes inequalities
- Nevanlinna parametrization of solutions
Further reading
- Web https://en.wikipedia.org/wiki/Moment_(mathematics), lead section
About this page
| Tag | 01XAHPADBA |
|---|---|
| URI | m2://01XAHPADBA |
| Aliases | moment-of-random-variable, raw-moment |
| Kind | concept |
| Writing | W1 stated |
| MSC | 60E05 |
| Same as |
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What this page needs for W2
- edge instance_of in: at least two examples (0 of 2)
- edge not_instance_of in: at least one non-example (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
Special cases
Definitions
Used by
- Log-normal distribution
- Pareto distribution
- Indeterminate moment problem
- Positivity of Hankel matrices of moments
- Moment problem
- Moments and orthogonal polynomials
- Hausdorff moment problem
- Berry–Esseen theorem
- Determinate moment problem
- Cumulant
- Moments of the log-normal distribution
- Krein's condition
- Vanishing moments of a wavelet
- Carleman's condition
- Hamburger moment problem
- Stieltjes moment problem
- Chebyshev–Markov–Stieltjes inequalities