Bochner theorem on characteristic functions
E613407
The Bochner theorem on characteristic functions is a fundamental result in probability theory and harmonic analysis that characterizes which functions are Fourier transforms of probability measures by requiring them to be positive-definite, continuous, and normalized at zero.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Bochner's theorem | 2 |
| Bochner theorem on characteristic functions canonical | 1 |
| Lévy–Khintchine formula | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6716265 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: Bochner theorem on characteristic functions Context triple: [Salomon Bochner, notableFor, Bochner theorem on characteristic functions]
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A.
Isserlis’ theorem in probability theory
Isserlis’ theorem in probability theory is a result that expresses higher-order moments of jointly Gaussian random variables in terms of sums of products of their pairwise covariances.
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B.
Khinchin's representation theorem
Khinchin's representation theorem is a result in probability theory that characterizes stationary stochastic processes by representing them in terms of simpler, more fundamental random components.
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C.
Wiener–Khinchin theorem
The Wiener–Khinchin theorem is a fundamental result in signal processing and probability theory that relates a wide-sense stationary random process’s autocorrelation function to its power spectral density via the Fourier transform.
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D.
Cameron–Martin theorem
The Cameron–Martin theorem is a fundamental result in probability theory and functional analysis that characterizes how Gaussian measures on infinite-dimensional spaces change under shifts by elements of a special Hilbert subspace (the Cameron–Martin space).
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E.
Tauberian theorems
Tauberian theorems are results in mathematical analysis that connect the behavior of transformed series or integrals (such as those summed by Abel or Cesàro methods) back to the asymptotic behavior or convergence of the original sequences or series.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Bochner theorem on characteristic functions Target entity description: The Bochner theorem on characteristic functions is a fundamental result in probability theory and harmonic analysis that characterizes which functions are Fourier transforms of probability measures by requiring them to be positive-definite, continuous, and normalized at zero.
-
A.
Isserlis’ theorem in probability theory
Isserlis’ theorem in probability theory is a result that expresses higher-order moments of jointly Gaussian random variables in terms of sums of products of their pairwise covariances.
-
B.
Khinchin's representation theorem
Khinchin's representation theorem is a result in probability theory that characterizes stationary stochastic processes by representing them in terms of simpler, more fundamental random components.
-
C.
Wiener–Khinchin theorem
The Wiener–Khinchin theorem is a fundamental result in signal processing and probability theory that relates a wide-sense stationary random process’s autocorrelation function to its power spectral density via the Fourier transform.
-
D.
Cameron–Martin theorem
The Cameron–Martin theorem is a fundamental result in probability theory and functional analysis that characterizes how Gaussian measures on infinite-dimensional spaces change under shifts by elements of a special Hilbert subspace (the Cameron–Martin space).
-
E.
Tauberian theorems
Tauberian theorems are results in mathematical analysis that connect the behavior of transformed series or integrals (such as those summed by Abel or Cesàro methods) back to the asymptotic behavior or convergence of the original sequences or series.
- F. None of above. chosen
Statements (42)
| Predicate | Object |
|---|---|
| instanceOf | mathematical theorem ⓘ |
| appliesTo |
functions on locally compact abelian groups
ⓘ
functions on the real line ⓘ |
| assumption |
function is bounded
ⓘ
function is continuous at zero ⓘ function is defined on a locally compact abelian group ⓘ function is normalized at zero ⓘ function is positive-definite ⓘ |
| characterizes |
Fourier transforms of finite positive measures
ⓘ
Fourier transforms of probability measures on the real line ⓘ |
| codomain | space of finite positive measures ⓘ |
| concerns |
Fourier transforms of probability measures
ⓘ
characteristic functions ⓘ |
| conclusion |
existence of a probability measure with given characteristic function
ⓘ
function is the Fourier transform of a unique finite positive measure ⓘ |
| domain | space of continuous positive-definite functions with value 1 at zero ⓘ |
| field |
harmonic analysis
ⓘ
probability theory ⓘ |
| guarantees |
existence of a representing measure
ⓘ
uniqueness of the representing measure ⓘ |
| hasVersion |
Bochner theorem for finite positive measures
NERFINISHED
ⓘ
Bochner theorem for probability measures NERFINISHED ⓘ Bochner theorem on locally compact abelian groups NERFINISHED ⓘ |
| historicalPeriod | 20th century mathematics ⓘ |
| implies |
every characteristic function is bounded by 1 in modulus
ⓘ
every characteristic function is positive-definite ⓘ every characteristic function is uniformly continuous ⓘ |
| isToolFor |
characterization of probability distributions via characteristic functions
ⓘ
representation of positive-definite functions as Fourier transforms ⓘ |
| mathematicalArea |
functional analysis
ⓘ
measure theory ⓘ |
| namedAfter | Salomon Bochner NERFINISHED ⓘ |
| normalizationCondition | value at zero equals 1 ⓘ |
| relatedTo |
Fourier–Stieltjes transform
NERFINISHED
ⓘ
Herglotz representation theorem NERFINISHED ⓘ Lévy continuity theorem NERFINISHED ⓘ |
| usedIn |
construction of probability measures from characteristic functions
ⓘ
harmonic analysis on locally compact abelian groups ⓘ study of infinitely divisible distributions ⓘ |
| usesConcept |
continuity
ⓘ
normalization at zero ⓘ positive-definite function ⓘ |
How these facts were elicited
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Subject: Bochner theorem on characteristic functions Description of subject: The Bochner theorem on characteristic functions is a fundamental result in probability theory and harmonic analysis that characterizes which functions are Fourier transforms of probability measures by requiring them to be positive-definite, continuous, and normalized at zero.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.