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  1. library('gamlss')
  2. library('foreach')
  3. library('doParallel')
  4.  
  5. registerDoParallel(cores = 4)
  6. # Generate data
  7. set.seed(314)
  8. sample.size <- 30
  9. input.processed.cut <- data.frame(TP = round(runif(sample.size) * 100),
  10.                                   FP = round(runif(sample.size) * 100),
  11.                                   x = runif(sample.size))
  12. # Fit Beta-binomial
  13. model3 <- gamlss(formula = cbind(TP, FP) ~ x,  
  14.                  family = BB,  
  15.                  data = input.processed.cut)
  16.  
  17. # Get the leave-one-out values
  18. loo_predict.mu <- function(model.obj, input.data) {
  19.   yhat <- foreach(i = 1 : nrow(input.data), .packages="gamlss", .combine = rbind) %dopar% {
  20.     updated.model.obj <- update(model.obj, data = input.data[-i, ])
  21.     predict(updated.model.obj, what = "mu", newdata = input.data[i,], type = "response")
  22.   }
  23.   return(data.frame(result = yhat[, 1], row.names = NULL))
  24. }
  25.  
  26. par.run <- loo_predict.mu(model3, input.processed.cut)
  27. # Error in { : task 1 failed - "object 'input.data' not found"
  28.  
  29. > version
  30.                _                          
  31. platform       x86_64-w64-mingw32          
  32. arch           x86_64                      
  33. os             mingw32                    
  34. system         x86_64, mingw32            
  35. status                                    
  36. major          3                          
  37. minor          4.3                        
  38. year           2017                        
  39. month          11                          
  40. day            30                          
  41. svn rev        73796                      
  42. language       R                          
  43. version.string R version 3.4.3 (2017-11-30)
  44. nickname       Kite-Eating Tree
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