Theorems · Inductive type · probability

ProbabilityTheory.IsGaussianProcess

{Ω : Type u_1} →
  {E : Type u_2} →
    {T : Type u_3} →
      {mΩ : MeasurableSpace Ω} →
        [MeasurableSpace E] →
          [TopologicalSpace E] →
            [inst : AddCommMonoid E] →
              [Module ℝ E] →
                (T → Ω → E) → autoParam (MeasureTheory.Measure Ω) ProbabilityTheory.IsGaussianProcess._auto_1 → Prop

A stochastic process is a Gaussian process if all its finite dimensional distributions are Gaussian.

Defined in

Mathlib.Probability.Distributions.Gaussian.IsGaussianProcess.Def

Cited by

29 results in Mathlib

Foundations

Depth 95 from the axioms · uses propext, Classical.choice, Quot.sound

Assumes

MeasurableSpaceTopologicalSpaceAddCommMonoidModule