PDSampler.jl
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test for node with linear thinning
In the helper function ls_updatepq!
, those lines:
bounce = fg.factors[fidx].nextevent(vcxf, vcvf)
acc = bounce.dobounce(g, vcvf)
while !acc
bounce = fg.factors[fidx].nextevent(vcxf, vcvf)
acc = bounce.dobounce(g, vcvf)
end
tauf = bounce.tau
the while !acc
is for the case of thinning (corresponds to the accept/reject step in thinning). This is valid of course (same code as BPS) but so far the test case in LBPS has been a multivariate gaussian for which acc==true
. For the sake of testing, one should
- define a chain with simple factors
- factors require thinning for sampling
- test the helper function with that.