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Project-declaredLean 4.33.0-rc1 · mathlib@0434c033

Generate From eq predictable

ProbabilityTheory.ElementaryPredictableSet.generateFrom_eq_predictable

Plain-language statement

The elementary predictable sets generate the predictable σ-algebra. Note that we require the time domain to have countably generated atTop so that each (t, ∞] can be written as a countable union of intervals (t, s].

Exact Lean statement

theorem generateFrom_eq_predictable [(Filter.atTop : Filter ι).IsCountablyGenerated] :
    MeasurableSpace.generateFrom {↑S | S : ElementaryPredictableSet 𝓕} = 𝓕.predictable

Formal artifact

Lean source

Canonical source
Full Lean sourceLean 4
theorem generateFrom_eq_predictable [(Filter.atTop : Filter ι).IsCountablyGenerated] :    MeasurableSpace.generateFrom {↑S | S : ElementaryPredictableSet 𝓕} = 𝓕.predictable := by  apply le_antisymm  · apply MeasurableSpace.generateFrom_le    rintro _ S, rfl    exact S.measurableSet_predictable  · apply measurableSpace_le_predictable_of_measurableSet    · intro B₀ hB₀      apply MeasurableSpace.measurableSet_generateFrom      use singletonBotProd hB₀, coe_singletonBotProd hB₀    · intro t B hB      obtain seq, _, tendsto := Filter.exists_seq_monotone_tendsto_atTop_atTop ι      have : Set.Ioi t = ⋃ n : , Set.Ioc t (seq n) := by        ext s        suffices  n, s  seq n by simpa using fun _  this        rw [Filter.tendsto_atTop_atTop] at tendsto        obtain n, h := tendsto s        exact n, h n le_rfl      rw [this, Set.iUnion_prod_const]      refine MeasurableSet.iUnion fun n  MeasurableSpace.measurableSet_generateFrom ?_      use IocProd t (seq n) hB, coe_IocProd _ _ hB
Project
Brownian motion
License
Apache-2.0
Commit
5077304f5e73
Source
BrownianMotion/StochasticIntegral/SimpleProcess.lean:805-825

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Related declarations

Project-declaredLean 4.33.0-rc1

Continuous Within At Iio indicator Ioc

continuousWithinAt_Iio_indicator_Ioc

Plain-language statement

The indicator of a half-open interval Ioc a b with constant value c is left-continuous: when approached from the left it is eventually constant, so it is continuous within Iio t at t for every t.

probabilitystochastic processesmeasure theory

Source project: Brownian motion

Person-level attribution pending.

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Project-declaredLean 4.33.0-rc1

Dense comap val nhds Within Ioi ne Bot

Dense.comap_val_nhdsWithin_Ioi_neBot

Project documentation

This is an auxillary lemma used to prove Dense.monotone_of_isRightContinuous. It is saying that if D is a dense set and a, b are two points such that a < b, then the comap of 𝓝[Set.Ioi a] a under the inclusion D → α is nontrivial. Note that a < b is necessary as this is clearly not true if a is a top element.

probabilitystochastic processesmeasure theory

Source project: Brownian motion

Person-level attribution pending.

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