coupled_cpm_chains: Coupled correlated pseudo-marginal chains
In lolmid/unbiased_intractable_targets: Debiased particle MCMC with couplings

Sample two CPM chains, each following single_kernel marginally, and coupled_kernel jointly, until min(max(tau, K), max_iterations), where tau is the first time at which the two chains meet (i.e. take the same value exactly). Or more precisely, they meet with a delay of one, i.e. X_t = Y_t-1. The chains are initialized from the distribution provided in rinit.

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coupled_cpm_chains(single_kernel, coupled_kernel, coupled_init, nparticles,
  nobs, iters_per_cycle = 1, K = 1, max_iterations = Inf,
  preallocate = 10, coupled_state = F)

`single_kernel`	function taking a state (in a vector) and an iteration, and returning a list with a key named `chain_state` and containing the next state.
`coupled_kernel`	function taking two states (in two vectors) and an iteration, and returning a list with keys `chain_state1` and `chain_state2`.
`K`	number of iterations desired (will be proportional to the computing cost if meeting occurs before `K`, default to 1).
`max_iterations`	number of iterations at which the function stops if it is still running (default to Inf).
`preallocate`	expected number of iterations, used to pre-allocate memory (default to 10).
`rinit`	function taking no arguments are returning an initial state for a Markov chain.