R Under development (unstable) (2025-11-16 r89026 ucrt) -- "Unsuffered Consequences"
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> cat("Testing for non duplicated results in seeded simulations")
Testing for non duplicated results in seeded simulations> 
> library(bkmrhat)
Loading required package: coda
Diagnostics and parallel chain functioning for Bayesian kernel machine regression
> set.seed(111)
> dat <- bkmr::SimData(n = 50, M = 4)
> y <- dat$y
> Z <- dat$Z
> X <- dat$X
> 
> future::plan(strategy = future::sequential)
> fitkm.list <- kmbayes_parallel(nchains=2, y = y, Z = Z, X = X, iter = 10,
+                                verbose = FALSE, varsel = TRUE)
Chain 1 
Iteration: 2 (20% completed; 0.00221 secs elapsed)
Iteration: 3 (30% completed; 0.01192 secs elapsed)
Iteration: 4 (40% completed; 0.0134 secs elapsed)
Iteration: 5 (50% completed; 0.0148 secs elapsed)
Iteration: 6 (60% completed; 0.01626 secs elapsed)
Iteration: 7 (70% completed; 0.01774 secs elapsed)
Iteration: 8 (80% completed; 0.01921 secs elapsed)
Iteration: 9 (90% completed; 0.02065 secs elapsed)
Iteration: 10 (100% completed; 0.0221 secs elapsed)
Chain 2 
Iteration: 2 (20% completed; 0.00137 secs elapsed)
Iteration: 3 (30% completed; 0.00292 secs elapsed)
Iteration: 4 (40% completed; 0.00441 secs elapsed)
Iteration: 5 (50% completed; 0.0059 secs elapsed)
Iteration: 6 (60% completed; 0.00735 secs elapsed)
Iteration: 7 (70% completed; 0.00882 secs elapsed)
Iteration: 8 (80% completed; 0.01029 secs elapsed)
Iteration: 9 (90% completed; 0.01175 secs elapsed)
Iteration: 10 (100% completed; 0.01321 secs elapsed)
> 
> rr = as.mcmc.list(fitkm.list)
> tt = all.equal(as.data.frame(rr[[1]]), as.data.frame(rr[[2]]))
> stopifnot(mode(tt)=="character")
> 
> 
> fitkm.list[[1]] = fitkm.list[[2]]
> badpred = SamplePred_parallel(fitkm.list, method="exact", Znew = dat$Z[1,], Xnew = dat$X[1,])
Chain 1 
Chain 2 
> ff = tapply(badpred$znew1, badpred$chain, mean)
> tt = all.equal(ff[1], ff[2])
> stopifnot(mode(tt)=="character")
> 
> proc.time()
   user  system elapsed 
   5.39    0.60    5.98