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- library('gamlss')
- library('foreach')
- library('doParallel')
- registerDoParallel(cores = 4)
- # Generate data
- set.seed(314)
- sample.size <- 30
- input.processed.cut <- data.frame(TP = round(runif(sample.size) * 100),
- FP = round(runif(sample.size) * 100),
- x = runif(sample.size))
- # Fit Beta-binomial
- model3 <- gamlss(formula = cbind(TP, FP) ~ x,
- family = BB,
- data = input.processed.cut)
- # Get the leave-one-out values
- loo_predict.mu <- function(model.obj, input.data) {
- yhat <- foreach(i = 1 : nrow(input.data), .packages="gamlss", .combine = rbind) %dopar% {
- updated.model.obj <- update(model.obj, data = input.data[-i, ])
- predict(updated.model.obj, what = "mu", newdata = input.data[i,], type = "response")
- }
- return(data.frame(result = yhat[, 1], row.names = NULL))
- }
- par.run <- loo_predict.mu(model3, input.processed.cut)
- # Error in { : task 1 failed - "object 'input.data' not found"
- > version
- _
- platform x86_64-w64-mingw32
- arch x86_64
- os mingw32
- system x86_64, mingw32
- status
- major 3
- minor 4.3
- year 2017
- month 11
- day 30
- svn rev 73796
- language R
- version.string R version 3.4.3 (2017-11-30)
- nickname Kite-Eating Tree
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