Khinchin's law of the iterated logarithm
E378993
Khinchin's law of the iterated logarithm is a fundamental result in probability theory that precisely characterizes the almost-sure fluctuations of partial sums of independent random variables on the scale of the square root of twice the product of their variance and the iterated logarithm of the sample size.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Khinchin's law of the iterated logarithm canonical | 3 |
| Hartman–Wintner law of the iterated logarithm | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3677820 — 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: Khinchin's law of the iterated logarithm Context triple: [Aleksandr Khinchin, notableWork, Khinchin's law of the iterated logarithm]
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A.
Khinchin–Kahane type inequalities
Khinchin–Kahane type inequalities are fundamental results in probability and functional analysis that bound moments or norms of random series (often with Rademacher or Gaussian coefficients) in terms of each other, providing powerful tools for studying the geometry of Banach spaces and random processes.
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B.
Kolmogorov zero–one law
The Kolmogorov zero–one law is a fundamental result in probability theory stating that certain events determined by the tail behavior of independent random variables must have probability either zero or one.
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C.
Kakutani’s random ergodic theorem
Kakutani’s random ergodic theorem is a fundamental result in ergodic theory that extends classical ergodic theorems to sequences of randomly chosen measure-preserving transformations.
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D.
Berry–Esseen theorem
The Berry–Esseen theorem is a quantitative refinement of the central limit theorem that provides explicit bounds on the rate of convergence of normalized sums of independent random variables to the normal distribution.
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E.
Newcomb–Benford law
The Newcomb–Benford law is a statistical principle stating that in many naturally occurring datasets, the leading digits are distributed logarithmically, with smaller digits (especially 1) appearing as the first digit more frequently than larger ones.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Khinchin's law of the iterated logarithm Target entity description: Khinchin's law of the iterated logarithm is a fundamental result in probability theory that precisely characterizes the almost-sure fluctuations of partial sums of independent random variables on the scale of the square root of twice the product of their variance and the iterated logarithm of the sample size.
-
A.
Khinchin–Kahane type inequalities
Khinchin–Kahane type inequalities are fundamental results in probability and functional analysis that bound moments or norms of random series (often with Rademacher or Gaussian coefficients) in terms of each other, providing powerful tools for studying the geometry of Banach spaces and random processes.
-
B.
Kolmogorov zero–one law
The Kolmogorov zero–one law is a fundamental result in probability theory stating that certain events determined by the tail behavior of independent random variables must have probability either zero or one.
-
C.
Kakutani’s random ergodic theorem
Kakutani’s random ergodic theorem is a fundamental result in ergodic theory that extends classical ergodic theorems to sequences of randomly chosen measure-preserving transformations.
-
D.
Berry–Esseen theorem
The Berry–Esseen theorem is a quantitative refinement of the central limit theorem that provides explicit bounds on the rate of convergence of normalized sums of independent random variables to the normal distribution.
-
E.
Newcomb–Benford law
The Newcomb–Benford law is a statistical principle stating that in many naturally occurring datasets, the leading digits are distributed logarithmically, with smaller digits (especially 1) appearing as the first digit more frequently than larger ones.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
law of the iterated logarithm
ⓘ
probability theorem ⓘ result in probability theory ⓘ |
| appliesTo |
independent identically distributed random variables with zero mean
ⓘ
random variables with finite nonzero variance ⓘ |
| assumes |
finite second moment
ⓘ
identical distribution of the summands ⓘ independence of the summands ⓘ |
| characterizes | almost-sure fluctuations of partial sums of independent random variables ⓘ |
| comparesWith |
central limit theorem scaling sqrt(n)
ⓘ
strong law of large numbers scaling n ⓘ |
| concerns |
almost sure convergence properties
ⓘ
partial sums of random variables ⓘ |
| describes |
asymptotic behavior of normalized partial sums
ⓘ
limiting envelope of normalized random walk paths ⓘ |
| field |
probability theory
ⓘ
stochastic processes ⓘ |
| gives |
exact liminf behavior of normalized partial sums
ⓘ
exact limsup behavior of normalized partial sums ⓘ |
| givesInformationOn |
maximal fluctuations of partial sums
ⓘ
oscillatory behavior of sums around zero ⓘ |
| historicalPeriod | early 20th century ⓘ |
| implies |
liminf of S_n divided by sqrt(2 σ² n log log n) equals -1 almost surely
ⓘ
limsup of S_n divided by sqrt(2 σ² n log log n) equals 1 almost surely ⓘ |
| isFormulatedFor | partial sums S_n = X_1 + ... + X_n ⓘ |
| isRelatedTo |
Brownian motion
ⓘ
Donsker's invariance principle ⓘ Khinchin's law of the iterated logarithm self-linksurface differs ⓘ
surface form:
Hartman–Wintner law of the iterated logarithm
Kolmogorov's law of the iterated logarithm ⓘ functional law of the iterated logarithm ⓘ |
| isSpecialCaseOf | Kolmogorov's law of the iterated logarithm ⓘ |
| isUsedIn |
asymptotic analysis of stochastic processes
ⓘ
empirical process theory ⓘ limit theory of random walks ⓘ probabilistic number theory ⓘ statistics of extremes of partial sums ⓘ |
| namedAfter | Aleksandr Khinchin ⓘ |
| normalizationInvolves | square root of 2 σ² n log log n ⓘ |
| refines |
central limit theorem
ⓘ
law of large numbers ⓘ
surface form:
strong law of large numbers
|
| requires | nondegenerate variance ⓘ |
| scaleOfFluctuations | square root of twice the variance times the iterated logarithm of sample size ⓘ |
| strengthens |
information provided by the central limit theorem about fluctuations
ⓘ
information provided by the strong law of large numbers about convergence ⓘ |
| typeOfLimit | almost sure limit theorem ⓘ |
| usesFunction | iterated logarithm log log n ⓘ |
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Subject: Khinchin's law of the iterated logarithm Description of subject: Khinchin's law of the iterated logarithm is a fundamental result in probability theory that precisely characterizes the almost-sure fluctuations of partial sums of independent random variables on the scale of the square root of twice the product of their variance and the iterated logarithm of the sample size.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.