Multivariate Gaussian distributions #
theorem
ProbabilityTheory.covMatrix_stdGaussian
{E : Type u_1}
[NormedAddCommGroup E]
[InnerProductSpace ℝ E]
[FiniteDimensional ℝ E]
[MeasurableSpace E]
[BorelSpace E]
:
theorem
ProbabilityTheory.inner_toEuclideanCLM
{ι : Type u_2}
[Fintype ι]
[DecidableEq ι]
{S : Matrix ι ι ℝ}
(x y : EuclideanSpace ℝ ι)
:
inner ℝ x ((Matrix.toEuclideanCLM S) y) = ⇑((EuclideanSpace.basisFun ι ℝ).toBasis.repr x) ⬝ᵥ S.mulVec ⇑((EuclideanSpace.basisFun ι ℝ).toBasis.repr y)
theorem
ProbabilityTheory.hasLaw_eval_multivariateGaussian
{ι : Type u_2}
[Fintype ι]
[DecidableEq ι]
{μ : EuclideanSpace ℝ ι}
{S : Matrix ι ι ℝ}
(hS : S.PosSemidef)
{i : ι}
:
HasLaw (fun (x : EuclideanSpace ℝ ι) => x.ofLp i) (gaussianReal (μ.ofLp i) (S i i).toNNReal) (multivariateGaussian μ S)