R Under development (unstable) (2024-03-14 r86117 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64

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> library(bfp)
> 
> set.seed (234)
> 
> ## setting where the error occured
> beta0 <- 1
> alpha1 <- 1
> alpha2 <- c (1, 1)
> delta1 <- 1
> 
> sampleSize <- c (40, 100)
> sigma2 <- c (4, 3, 2, 1)
> hyperpara <- c (3.05, 3.4, 3.7, 3.95)
> 
> h <- 1
> i <- 4
> j <- 4
> 
> thisN <- sampleSize[h]
> 
> x <- matrix (runif (thisN * 3, 1, 4), nrow = thisN, ncol = 3) # predictor values
> w <- matrix (rbinom (thisN * 2, size = 1, prob = 0.5), nrow = thisN, ncol = 2)
> 
> covData <- data.frame (x = x, w = w)# start data frame
> 
> x1tr <- alpha1 * x[,1]^2
> x2tr <- cbind (x[,2]^-0.5, x[,2]^-0.5 * log (x[,2])) %*% alpha2
> w1tr <- delta1 * w[,1]
> 
> predictorTerms <- x1tr + x2tr + w1tr # linear predictor
>     
> thisPriorSpecs <- list(a = hyperpara[i],
+                        modelPrior="sparse")
>         
> covData$y <- predictorTerms + rnorm (thisN, 0, sqrt (sigma2[j]))
> 
> ## try it:
> modelNow <- BayesMfp (y ~ bfp (x.1) + bfp (x.2) + bfp (x.3) + uc (w.1) + uc (w.2),
+                       data = covData,
+                       priorSpecs = thisPriorSpecs,
+                       method = "exhaustive"
+                       )
Starting with computation of every model...
0%______________________________________________________________________________________________100%
----------------------------------------------------------------------------------------------------
Actual number of possible models:  364500 
Number of non-identifiable models: 0
Number of saved possible models:   3645
> 
> proc.time()
   user  system elapsed 
  11.70    0.09   11.78