tulpaObs 0.0.185

0.0.185 (2026-08-07)

• Pinned to tulpa (>= 0.0.131) so the auto-recentering outer grid also
  engages at this package's own defaults (gcol33/tulpa#291, #292). The
  0.0.130 rescue that 0.0.183 pinned for read pareto_k_mode_u / cov_u,
  fields only the full outer Pareto-k diagnostic populates -- and
  control$diagnose.k defaults to FALSE on every route reaching the joint
  driver -- occu_cover(), occu_multiscale_cover(), and occu()'s
  SVC-bar joint path (#101) -- so the driver's rescue never fired on a
  default fit. It now computes the same (mode, covariance) itself
  whenever the grid has collapsed onto an edge, independent of the
  diagnostic. A collapsed default occu_cover() fit therefore re-centers and
  refits where before it stayed railed.

  The companion upstream change adds the same rescue to fit_st_nested()'s
  tau_spatial x tau_temporal [x rho] tensor grid, which reaches the
  observation families carrying an areal + temporal field on one arm
  (removal(), distance(), fp_occu(), dyn_abun()).

  Both are behaviour-preserving where the grid was not collapsed, and both
  decline whenever a grid-construction knob was set explicitly. The
  Remotes: gcol33/tulpa@v0.0.131 tag moves with the floor, as
  check-engine-pin.R asserts: r-universe builds default-branch HEAD on its
  own poll schedule and currently serves 0.0.130, so the tag is what resolves
  the pinned engine.

0.0.184 (2026-08-07)

• tobs_cpo(), tobs_ppc() and tobs_pit_residuals() now work on a compact
  (ragged) occu_cover() fit (#185). method = "nested_laplace" defaults
  compact = TRUE, so the ragged carrier is the standard representation for the
  joint engine, and a compact fit stores no padded [n_sites x max_visits]
y / valid grid. The pointwise-log-likelihood path already read the ragged
  carrier, but the PPC and the PIT / LOO-PIT CDF limits still derived their
  per-site detection summary as rowSums(model$y * model$valid), which errored
  with 'x' must be an array of at least two dimensions. LOO / CPO / LOO-PIT and
  the posterior predictive check were therefore unavailable for any real-scale
  occu_cover() fit while tobs_waic() worked.

  All three now read one .occu_cover_visit_view(): the one-row-per-valid-visit
  structure a compact fit stores, and the flattening of a dense fit's padded grid
  (.occu_cover_dense_ragged(), the site-major visit-ascending order the
  pointwise kernel already used). n_valid and any_det are derived there, so
  there is one definition of each. Because both layouts now feed one kernel per
  diagnostic, the dense and compact builds of the same data agree to the bit:
  measured 0.000e+00 across elpd_waic, elpd_loo, the LOO-PIT, the PIT
  residuals, and the PPC fit.y / fit.y.rep / bayesian.p.

• tobs_ppc() no longer returns NA when a detected visit has a missing
  cover (#185). The likelihood gates the cover density on detected AND finite (missing-at-random cover), but the PPC kernel scored the NA into the
  Freeman-Tukey / chi-squared sum, so fit.y came back NA for every draw and
  bayesian.p with it. Verified directly against the pre-change kernel: one NA
  cover at one detected visit took fit.y from 1.788 to NA on all draws.
  The replicate is now drawn at every valid visit (so the RNG stream does not
  depend on which visits happened to be detected) and scored only where a cover
  was observed.

• Internal: the three ragged occu_cover() kernels -- pointwise
  log-likelihood, PPC, CDF limits -- assemble their per-draw predictors from one
  shared Arms view (src/occu_cover_ragged.h) instead of each writing out the
  column-major design / draw index arithmetic. The pointwise kernel is
  byte-identical after the change (test-occu-cover-ploglik-cpp.R scores it
  against its R oracle). The PPC kernel now takes the arm designs and the
  coefficient draws rather than precomputed [n_sites x (S * max_visits)]
  predictor blocks, so its memory is O(V) in the observations rather than
  O(padded grid x draws).