Zulip Chat Archive
Stream: Is there code for X?
Topic: wikipedia flavored stochastic_process
Lars Ericson (Jan 20 2021 at 20:25):
For the Wikipedia definition of stochastic process, is the following rendition reasonable, and in terms of mathlib
style guide, how would you touch it up:
import measure_theory.lebesgue_measure
import measure_theory.measurable_space
open measure_theory
-- https://en.wikipedia.org/wiki/Probability_space
class probability_space (α : Type*) extends measure_space α :=
(is_probability_measure: probability_measure volume)
-- https://en.wikipedia.org/wiki/Random_variable#Definition
def random_variable (α β: Type*) (PS: probability_space α) (MS: measurable_space β):=
@measurable α β PS.to_measure_space.to_measurable_space MS
--https://en.wikipedia.org/wiki/Stochastic_process#Stochastic_process
def stochastic_process (α β T: Type*) (PS: probability_space α) (MS: measurable_space β) (X: T → α → β) (t: T) :=
random_variable α β PS MS (X t)
-- https://en.wikipedia.org/wiki/Stochastic_process#Index_set
def index_set (α β T: Type*) (X: T → α → β) := T
-- https://en.wikipedia.org/wiki/Stochastic_process#State_space
def state_space (α β T: Type*) (X: T → α → β) := β
-- https://en.wikipedia.org/wiki/Stochastic_process#Sample_function
def sample_function (α β T: Type*) (X: T → α → β) := λ (ω: α), λ (t: T), X t ω
-- https://en.wikipedia.org/wiki/Stochastic_process#Law
def law (α β T: Type*)
(PS: probability_space α)
(MS: measurable_space β)
(X: T → α → β)
(t: T)
(SP: stochastic_process α β T PS MS X t)
(HM: has_mem β β)
(Y: set β):=
PS.volume.to_outer_measure.measure_of {ω : α | ∃ y:β, X t ω ∈ y}
Last updated: Dec 20 2023 at 11:08 UTC