The maximal Metropolis–Hastings kernel satisfies detailed balance
ProvedTierneyMH.Mixture.maxMHKernel_reversiblemarkov-chain-monte-carlomarkov-kernelmetropolis-hastingsp2o-batch-p200bp2o-gran-per-chapterp2o-plan-paperp2o-v1
Let be a probability measure and a Markov proposal kernel on a measurable space . The maximal Metropolis–Hastings kernel for , the kernel (1) with acceptance probability , satisfies the detailed balance relation
as measures on . In particular is invariant for .
In the paper this follows from the fact that satisfies conditions (i) and (ii) together with Theorem 2. It is what makes the off-diagonal ordering of Proposition 5 a comparison between kernels with invariant distribution , as the definition of presupposes.
Formalization Note Detailed balance is Mathlib's Kernel.IsReversible: for all measurable .
Preamble
import Mathlib import Definitions.Def_TierneyMH_Mixture_maxMHKernel open MeasureTheory ProbabilityTheory open scoped ENNReal
Formal statement
namespace TierneyMH.Mixture
/-- **The maximal Metropolis–Hastings kernel is reversible** (Tierney 1998, §2, p. 3:
`α_MH` satisfies (i)–(ii), so by Theorem 2 the kernel satisfies detailed balance).
For a probability measure `π` and a Markov proposal kernel `Q`, the kernel (1) with
acceptance probability `α_MH` satisfies the detailed balance relation (2),
`π(dx) P(x, dy) = π(dy) P(y, dx)`. -/
theorem maxMHKernel_reversible {E : Type*} [MeasurableSpace E]
(π : Measure E) [IsProbabilityMeasure π] (Q : Kernel E E) [IsMarkovKernel Q] :
Kernel.IsReversible (maxMHKernel π Q) π := by sorry
end TierneyMH.Mixture
Source
L. Tierney, A Note on Metropolis–Hastings Kernels for General State Spaces, Ann. Appl. Probab. 8(1) (1998) 1–9, DOI 10.1214/aoap/1027961031, p. 3, §2 (α_MH satisfies (i)–(ii); by Theorem 2 the maximal kernel is reversible)
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.