[R] missing values error in if statement

Rui Barradas ru|pb@rr@d@@ @end|ng |rom @@po@pt
Fri May 20 16:47:29 CEST 2022


Hello,

After a sequence of getAnywhere instructions


capture.output(
   getAnywhere("plot.fairness_object"),
   file = "~/Temp/plot_fairness_object.txt"
)
getAnywhere("get_nice_ticks")
getAnywhere("readable_number")


to try to get to the offending function, here is what I found out.

1. The plot method for objects of S3 class "fairness_object" is defined 
in package fairmodels;
2. The error only occurs with fairness_metrics = "FPR";
3. The error comes from readable_number in package fairmodels;
4. It's the 2nd time this year [1] R-Help gets a question with the error

Error in if (fraction <= 1) { : missing value where TRUE/FALSE needed

5. The call sequence is

plot.fairness_object > get_nice_ticks > readable_number

all in package fairmodels;



You should then write maintainer("fairmodels") explaining your problem, 
with a link to the start of this thread, but start your code with calls 
to library() to load the necessary packages for the code to run.

 From point 2 above,


fairness_metrics <- c("ACC", "TPR", "PPV", "FPR", "STP")
plot(fc, fairness_metrics = fairness_metrics[4])   # FPR, error


Assign any value but 4 to i_fm and you can plot the object fc.

i_fm <- 1
plot(fc, fairness_metrics = fairness_metrics[i_fm])  # OK


[1] https://www.mail-archive.com/r-help@r-project.org/msg264726.html

Hope this helps,

Rui Barradas


Às 14:12 de 20/05/2022, Neha gupta escreveu:
> When I run
> 
> print(fc)
> 
> it shows 'Inf'. It mean it doesn't calculate the bias/fairness, maybe 
> due to missing values.
> 
> RF passes 1/5 metrics
> Total loss :  Inf
> 
> 
> 
> On Fri, May 20, 2022 at 3:06 PM Rui Barradas <ruipbarradas using sapo.pt 
> <mailto:ruipbarradas using sapo.pt>> wrote:
> 
>     Hello,
> 
>     This is a frequent way of coding and a source for questions.
> 
> 
>     ifelse(test$CE == '2', 1, 0)
> 
> 
>     is equivalent to the much more performant
> 
> 
>     as.integer(test$CE == '2')   # or as.numeric
> 
> 
>     If the code still runs with errors, then those errors came from
>     elsewhere.
> 
>     Hope this helps,
> 
>     Rui Barradas
> 
> 
>     Às 09:16 de 20/05/2022, Neha gupta escreveu:
>      > I am sorry.. The code is here and data is provided at the end of this
>      > email.
>      >
>      > data = readARFF("aho.arff")
>      >
>      > index= sample(1:nrow(data), 0.7*nrow(data))
>      > train= data[index,]
>      > test= data[-index,]
>      >
>      > task = TaskClassif$new("data", backend = train, target = "isKilled")
>      > learner= lrn("classif.randomForest", predict_type = "prob")
>      > model= learner$train(task )
>      >
>      > ///explainer is created to identify a bias in a particular
>     feature i.e. CE
>      > feature in this case
>      >
>      > explainer = explain_mlr3(model,
>      >                           data = test[,-15],
>      >                           y = as.numeric(test$isKilled)-1,
>      >                           label="RF")
>      > prot <- ifelse(test$CE == '2', 1, 0)       /// Error comes here
>      > privileged <- '1'
>      >
>      >
>      > fc= fairness_check(explainer,
>      >                            protected = prot,
>      >                     privileged = privileged)
>      > plot(fc)
>      >
>      >
>      > ////////////////////////////////////////// my data is
>      >
>      > dput(test)
>      > structure(list(DepthTree = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2,
>      > 2, 2, 2, 1, 1, 1, 1, 2, 1), NumSubclass = c(0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2), McCabe = c(1, 1, 1,
>      > 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 1, 2, 2, 1,
>      > 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5,
>      > 5, 5, 5, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 5, 5, 5, 5, 5, 5,
>      > 5, 5, 5, 5, 5, 5, 2, 2, 2, 2, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
>      > 5, 5, 5, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 4, 4, 1, 1, 2, 2, 2, 2,
>      > 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1), LOC = c(3,
>      > 3, 4, 10, 10, 10, 10, 4, 5, 22, 22, 22, 22, 22, 22, 22, 22, 3,
>      > 3, 3, 3, 8, 8, 4, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23,
>      > 23, 23, 23, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 8, 8,
>      > 16, 16, 16, 16, 16, 16, 16, 16, 16, 20, 20, 20, 20, 20, 20, 20,
>      > 20, 20, 20, 20, 20, 7, 7, 7, 7, 18, 18, 18, 18, 18, 18, 15, 15,
>      > 15, 15, 15, 15, 15, 15, 6, 6, 6, 15, 15, 15, 15, 15, 15, 9, 9,
>      > 9, 9, 9, 9, 9, 4, 4, 3, 3, 3, 3, 4, 4, 4, 5, 8, 8, 3, 3, 3, 7,
>      > 7, 3, 3, 15, 15, 15, 15, 15, 15, 15, 15, 3, 3, 3, 4, 4, 4, 4,
>      > 8, 8, 8, 8, 4, 3), DepthNested = c(1, 1, 1, 2, 2, 2, 2, 1, 2,
>      > 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 2, 2, 1, 3, 3, 3, 3, 3, 3,
>      > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
>      > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
>      > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2,
>      > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1,
>      > 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1), CA = c(1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
>      > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
>      > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
>      > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
>      > 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2,
>      > 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1), CE = c(2, 2, 2, 2, 2,
>      > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
>      > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
>      > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 2, 2), Instability = c(0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0.667, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.667, 0.667, 0.667,
>      > 0.667, 0.667, 0.667, 0.667, 0, 0, 0, 0, 0.667, 0.667), numCovered
>     = c(0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 123, 54, 54,
>      > 54, 123, 54, 54, 39, 84, 54, 54, 15, 138, 189, 189, 189, 27,
>      > 51, 33, 6, 27, 27, 150, 150, 150, 54, 150, 54, 54, 150, 117,
>      > 51, 66, 60, 15, 15, 72, 12, 45, 255, 255, 129, 129, 129, 0, 129,
>      > 0, 0, 6, 6, 6, 303, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 15, 12,
>      > 12, 12, 18, 12, 12, 48, 12, 1557, 48, 12, 171, 0, 0, 0, 141,
>      > 141, 45, 141, 18, 39), operator = structure(c(4L, 13L, 13L, 1L,
>      > 4L, 9L, 12L, 4L, 11L, 4L, 7L, 8L, 8L, 8L, 8L, 8L, 9L, 7L, 8L,
>      > 8L, 6L, 7L, 8L, 4L, 1L, 2L, 3L, 4L, 7L, 8L, 8L, 8L, 8L, 8L, 9L,
>      > 11L, 12L, 12L, 4L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 6L, 9L,
>      > 9L, 4L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 10L, 1L, 1L, 1L, 7L, 7L,
>      > 8L, 8L, 8L, 8L, 8L, 13L, 13L, 7L, 8L, 8L, 9L, 8L, 8L, 8L, 8L,
>      > 9L, 10L, 1L, 4L, 4L, 6L, 7L, 8L, 8L, 8L, 9L, 10L, 10L, 7L, 8L,
>      > 8L, 10L, 11L, 11L, 7L, 8L, 4L, 8L, 9L, 10L, 10L, 4L, 10L, 7L,
>      > 7L, 10L, 6L, 8L, 8L, 10L, 8L, 8L, 10L, 9L, 8L, 10L, 7L, 7L, 13L,
>      > 2L, 2L, 2L, 8L, 8L, 8L, 8L, 8L, 11L, 10L, 10L, 13L, 13L, 8L,
>      > 8L, 8L, 6L, 7L, 8L, 10L, 13L, 13L), .Label = c("T0", "T1", "T2",
>      > "T3", "T4", "T5", "T6", "T7", "T8", "T9", "T10", "T11", "T12",
>      > "T13", "T14", "T15"), class = "factor"), methodReturn =
>     structure(c(2L,
>      > 2L, 2L, 2L, 2L, 2L, 2L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>      > 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
>      > 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>      > 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L,
>      > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L,
>      > 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
>      > 4L, 4L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 1L, 4L,
>      > 4L, 4L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 4L, 4L, 4L, 4L,
>      > 4L, 4L, 4L, 4L, 3L, 3L, 2L, 2L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 2L,
>      > 2L), .Label = c("I", "V", "Z", "method", "D", "[D", "[[D", "J",
>      > "[I", "C", "[J", "[C", "[S", "F", "[F", "[B", "S", "B", "[Z",
>      > "[[S", "[[B", "[[Z"), class = "factor"), numTestsCover = c(16,
>      > 16, 16, 15, 15, 16, 15, 4, 16, 16, 15, 16, 15, 15, 15, 15, 15,
>      > 3, 3, 3, 2, 16, 11, 4, 16, 3, 16, 16, 16, 16, 16, 4, 16, 16,
>      > 16, 4, 16, 16, 3, 3, 3, 2, 4, 3, 2, 1, 4, 1, 15, 16, 15, 2, 3,
>      > 2, 3, 3, 2, 2, 2, 3, 4, 5, 5, 5, 4, 5, 5, 4, 4, 5, 5, 4, 4, 4,
>      > 4, 4, 4, 4, 4, 2, 4, 4, 4, 4, 4, 5, 4, 5, 5, 4, 4, 4, 4, 4, 4,
>      > 4, 4, 3, 4, 4, 4, 6, 6, 6, 0, 6, 0, 0, 2, 2, 2, 7, 0, 0, 0, 15,
>      > 16, 16, 16, 15, 17, 17, 17, 15, 5, 4, 4, 4, 3, 4, 4, 3, 4, 16,
>      > 16, 4, 17, 0, 0, 0, 5, 5, 3, 5, 2, 3), mutantAssert = c(55, 55,
>      > 55, 55, 55, 55, 55, 13, 55, 55, 55, 55, 55, 55, 55, 55, 55, 9,
>      > 9, 9, 9, 55, 41, 13, 55, 5, 55, 55, 55, 55, 55, 13, 55, 55, 55,
>      > 13, 55, 55, 13, 13, 13, 8, 13, 13, 8, 4, 13, 4, 55, 55, 55, 9,
>      > 9, 9, 9, 9, 9, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
>      > 9, 9, 9, 9, 9, 9, 5, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
>      > 9, 9, 9, 6, 9, 9, 9, 14, 14, 14, 0, 14, 0, 0, 2, 2, 2, 15, 0,
>      > 0, 0, 55, 58, 58, 55, 55, 58, 58, 58, 55, 9, 6, 6, 6, 6, 6, 6,
>      > 6, 6, 55, 55, 13, 57, 0, 0, 0, 11, 11, 7, 11, 9, 9), classAssert
>     = c(3,
>      > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
>      > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
>      > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
>      > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 10, 10, 10,
>      > 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 3, 3, 3, 3, 3, 3,
>      > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 1, 1, 1, 1, 3, 3,
>      > 3, 3, 0, 0), isKilled = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L,
>      > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>      > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>      > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>      > 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
>      > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L,
>      > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
>      > 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>      > 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L,
>      > 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("yes",
>      > "no"), class = "factor")), row.names = c(3L, 4L, 5L, 7L, 9L,
>      > 17L, 20L, 21L, 26L, 28L, 32L, 33L, 40L, 43L, 45L, 49L, 54L, 62L,
>      > 64L, 65L, 70L, 75L, 77L, 81L, 84L, 86L, 88L, 89L, 93L, 95L, 97L,
>      > 99L, 101L, 102L, 106L, 111L, 112L, 113L, 118L, 122L, 125L, 128L,
>      > 129L, 134L, 141L, 142L, 143L, 146L, 156L, 168L, 169L, 174L, 178L,
>      > 179L, 182L, 184L, 185L, 192L, 193L, 195L, 197L, 198L, 199L, 203L,
>      > 205L, 209L, 211L, 215L, 216L, 218L, 220L, 224L, 227L, 228L, 230L,
>      > 233L, 243L, 244L, 246L, 247L, 251L, 252L, 259L, 262L, 263L, 265L,
>      > 270L, 273L, 274L, 275L, 284L, 285L, 286L, 291L, 296L, 297L, 300L,
>      > 301L, 306L, 314L, 316L, 322L, 328L, 331L, 332L, 333L, 336L, 341L,
>      > 346L, 347L, 348L, 360L, 363L, 366L, 367L, 383L, 392L, 395L, 398L,
>      > 404L, 408L, 409L, 410L, 420L, 421L, 426L, 428L, 434L, 437L, 438L,
>      > 440L, 441L, 447L, 449L, 450L, 452L, 454L, 457L, 458L, 459L, 463L,
>      > 465L, 469L, 471L, 472L, 483L), class = "data.frame")
>      >
>      > On Fri, May 20, 2022 at 12:20 AM Jeff Newmiller
>     <jdnewmil using dcn.davis.ca.us <mailto:jdnewmil using dcn.davis.ca.us>>
>      > wrote:
>      >
>      >> Not reproducible. Posted HTML.
>      >>
>      >> On May 19, 2022 2:30:58 PM PDT, Neha gupta
>     <neha.bologna90 using gmail.com <mailto:neha.bologna90 using gmail.com>>
>      >> wrote:
>      >>> Why do I get the following error when my variable in the 'if
>     statement'
>      >> has
>      >>> no missing values.
>      >>>
>      >>> I check with is.na <http://is.na>(my variable) and it has no
>     missing values
>      >>>
>      >>> Error in if (fraction <= 1) { : missing value where TRUE/FALSE
>     needed
>      >>>
>      >>> Best regards
>      >>>
>      >>>        [[alternative HTML version deleted]]
>      >>>
>      >>> ______________________________________________
>      >>> R-help using r-project.org <mailto:R-help using r-project.org> mailing list
>     -- To UNSUBSCRIBE and more, see
>      >>> https://stat.ethz.ch/mailman/listinfo/r-help
>     <https://stat.ethz.ch/mailman/listinfo/r-help>
>      >>> PLEASE do read the posting guide
>      >> http://www.R-project.org/posting-guide.html
>     <http://www.R-project.org/posting-guide.html>
>      >>> and provide commented, minimal, self-contained, reproducible code.
>      >>
>      >> --
>      >> Sent from my phone. Please excuse my brevity.
>      >>
>      >
>      >       [[alternative HTML version deleted]]
>      >
>      > ______________________________________________
>      > R-help using r-project.org <mailto:R-help using r-project.org> mailing list
>     -- To UNSUBSCRIBE and more, see
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>     <https://stat.ethz.ch/mailman/listinfo/r-help>
>      > PLEASE do read the posting guide
>     http://www.R-project.org/posting-guide.html
>     <http://www.R-project.org/posting-guide.html>
>      > and provide commented, minimal, self-contained, reproducible code.
>



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