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Diff — Central limit theorem

Revision #2226 → #2878 · back to history

modifiedCentral limit theorem (informal)538b179931e6
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noteThe informal statement matches Mathlib's 1D i.i.d. CLT giving convergence in distribution of the standardized sum to a Gaussian.Verified: `tendstoInDistribution_inv_sqrt_mul_sum_sub` in `Mathlib/Probability/CentralLimitTheorem.lean` is Mathlib's 1D i.i.d. CLT giving convergence in distribution of the normalized sum to a Gaussian.
modifiedCLT statistical statement88a3f8f9a89a
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noteThe standard CLT statement is formalized via `tendstoInDistribution_inv_sqrt_mul_sum_sub` to `gaussianReal`.Verified: the standard CLT statement is `tendstoInDistribution_inv_sqrt_mul_sum_sub` with target `gaussianReal`.
modifiedLaw of large numbers (sample average)8c17ce194a4b
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noteAlmost-sure convergence of the sample average is Mathlib's strong law of large numbers.Verified: `strong_law_ae_real` in `Mathlib/Probability/StrongLaw.lean` gives a.s. convergence of the sample average.
modifiedLyapunov CLT02c1d31e2d6f
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noteNo Lyapunov condition or Lyapunov CLT appears in Mathlib (loogle returns 0 hits for `Lyapunov`).Verified: no `Lyapunov`-named declaration in Mathlib and no Lyapunov CLT.
modifiedLindeberg condition709fe4ba5121
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noteLoogle finds no declaration whose name contains `Lindeberg`.Verified: no declaration containing `Lindeberg` in Mathlib.
modifiedBerry–Esseen type bound for multivariate CLT4fa6b3b85b61
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noteNo Berry–Esseen bound (univariate or multivariate) is in Mathlib.Verified: no `BerryEsseen`/`Berry_Esseen` declaration in Mathlib.
modifiedCramér–Wold theoremf6162240a4da
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noteThe Cramér–Wold device is not formalized (loogle returns 0 hits for `CramerWold`).Verified: no `CramerWold`/`Cramer_Wold` declaration in Mathlib.
modifiedMartingale difference CLTc708422267a1
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noteMathlib has martingale theory but no martingale CLT (loogle finds no `centralLimit`/martingale match).Mathlib has martingale theory but no martingale CLT is present.
modifiedProof of classical CLT via characteristic functions85733343d51f
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noteMathlib's proof goes via characteristic functions with this key pointwise limit and Lévy's continuity theorem.Verified: this is the pointwise limit of characteristic functions used with Lévy's continuity theorem in Mathlib's CLT proof.
modifiedLévy's continuity theorem4e9c12f10bd3
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noteLévy's continuity theorem is formalized as the equivalence between weak convergence and pointwise convergence of characteristic functions.Verified: `ProbabilityMeasure.tendsto_iff_tendsto_charFun` is Lévy's continuity theorem.
modifiedLaw of the iterated logarithmb7cf937424f2
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noteThe law of the iterated logarithm is not formalized in Mathlib.Verified: no `IteratedLog` or `iteratedLogarithm` declaration in Mathlib.
modifiedStable distribution7c8cefaeb3f4
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noteStable distributions are not defined in Mathlib (only Cauchy and Gaussian are present).Verified: no stable distribution defined in Mathlib.
modifiedCLT restated via characteristic functions9ad4f88c98f4
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noteMathlib expresses the characteristic function of the normalized sum as a power and shows it converges to the Gaussian char function.Verified: `charFun_inv_sqrt_mul_sum` expresses the char function of the normalized sum as a power, converging to the Gaussian char function.
modifiedMultiplicative CLT (Gibrat's law)223932743036
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noteNo log-normal distribution or multiplicative CLT is in Mathlib.Verified: no log-normal distribution or multiplicative CLT in Mathlib.
modifiedConvergence in distribution612e2878f4e5
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noteWeak convergence of probability measures (convergence in distribution) is formalized via the topology on `ProbabilityMeasure`.Verified: weak convergence of probability measures characterized via bounded continuous integrals.
modifiedMultivariate normal (Gaussian) distributionec4d86cabbdd
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noteMultivariate Gaussian distributions are defined in Mathlib though no multidimensional CLT targets them.Verified: `multivariateGaussian μ S` defined on `EuclideanSpace ℝ ι`.
modifiedCharacteristic function of a random variable222fb5847931
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noteThe characteristic function E[e^{itX}] is formalized as `MeasureTheory.charFun` (module corrected to `…CharacteristicFunction.Basic`).Verified: `charFun μ t = ∫ x, exp (⟪x, t⟫ * I) ∂μ`.
addedNormal (Gaussian) distribution on ℝ303e3f8b81df
addedIndependent and identically distributed random variablesb6d00e78d305
addedAlmost sure convergence44a79d66a563
addedConvolution of probability densities0a7d801f63a8
addedTotal variation distance of measures7540447518a1