Last updated on 2020-08-07 01:50:31 CEST.
| Package | ERROR | OK |
|---|---|---|
| RBtest | 1 | 11 |
Current CRAN status: ERROR: 1, OK: 11
Version: 1.1
Check: examples
Result: ERROR
Running examples in 'RBtest-Ex.R' failed
The error most likely occurred in:
> ### Name: RBtest.iter
> ### Title: Test of missing data mechanism using all available information
> ### Aliases: RBtest.iter
>
> ### ** Examples
>
>
> set.seed(60)
> n<-100 # sample size
> r<-5 # number of variables
> mis<-0.2 # frequency of missing data
> mydata<-matrix(NA, nrow=n, ncol=r) # mydata is a matrix of r variables
> # following a U(0,1) distribution
> for (i in c(1:r)){
+ mydata[,i]<-runif(n,0,1)
+ }
> bin.var<-sample(LETTERS[1:2],n,replace=TRUE, prob=c(0.3,0.7)) # binary variable [A,B].
> # The probability of being in one of the categories is 0.3.
> cat.var<-sample(LETTERS[1:3],n,replace=TRUE, prob=c(0.5,0.3,0.2)) # categorical variable [A,B,C].
> # The vector of probabilities of occurence A, B and C is (0.5,0.3,0.7).
> num.var<-runif(n,0,1) # Additional continuous variable following a U(0,1) distribution
> mydata<-cbind.data.frame(mydata,bin.var,cat.var,num.var,stringsAsFactors = TRUE)
> # dataframe with r+3 variables
> colnames(mydata)=c("v1","v2","X1","X2","X3","X4","X5", "X6") # names of columns
> # MCAR on X1 and X4 by using v1 and v2. MAR on X3 and X5 by using X2 and X6.
> mydata$X1[which(mydata$v1<=sort(mydata$v1)[mis*n])]<-NA # X1: (mis*n)% of MCAR data.
> # All data above the (100-mis)th percentile in v1 are selected
> # and the corresponding observations in X1 are replaced with missing data.
> mydata$X3[which(mydata$X2<=sort(mydata$X2)[mis*n])]<-NA # X3: (mis*n)% of MAR data.
> # All data above the (100-mis)th percentile in X2 are selected
> # and the corresponding observations in X3 are replaced with missing data.
> mydata$X4[which(mydata$v2<=sort(mydata$v2)[mis*n])]<-NA # X4: (mis*n)% of MCAR data.
> # All data above the (100-mis)th percentile in v2 are selected
> # and the corresponding observations in X4 are replaced with missing data.
> mydata$X5[which(mydata$X6<=sort(mydata$X6)[mis*n])]<-NA # X5: (mis*n)% of MAR data.
> # All data above the (100-mis)th percentile in X6 are selected
> # and the corresponding observations in X5 are replaced with missing data.
> mydata$v1=NULL
> mydata$v2=NULL
>
> RBtest.iter(mydata,5)
Error in matcher(yhatobs, yhatmis, k = donors) :
function 'enterRNGScope' not provided by package 'Rcpp'
Calls: RBtest.iter ... sampler.univ -> do.call -> mice.impute.pmm -> matcher
Execution halted
Flavor: r-release-windows-ix86+x86_64