Probability theory and stochastic processes Foundations: probability spaces and events Concept
Probability density function
Summary
A probability density function of a real random variable is a nonnegative function with this property. For each set of values, the integral of over is the probability that lies in . The node probability density function gives the precise definition.
Where this leads
13 pages build on this one.
Further reading
About this page
| Tag | 0ZY9DX8FBF |
|---|---|
| URI | m2://0ZY9DX8FBF |
| Aliases | pdf, density-function, density |
| 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)
- edge specializes both: the more general notions and the special cases (0 of 1)
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What links here
Definitions
Used by
- Ziggurat algorithm
- von Mises–Fisher distribution
- Hamiltonian Monte Carlo
- Importance sampling
- Log-normal distribution
- Pareto distribution
- Fokker–Planck equation
- Borel–Kolmogorov paradox
- Mixture model
- Hazard function
- Rejection sampling
- Pitman–Koopman–Darmois theorem