[R] grubbs test to detect all outliers

[Rui Barradas]

Às 14:09 de 28/04/2023, AbouEl-Makarim Aboueissa escreveu:
> *R: *Grubbs Test to detect all outliers Per group for all columns in a data
> frame
> 
> 
> 
> Dear All: good morning
> 
> I have a dataset (as an example) with two column factors (factor1 and
> factor2) and 5 numerical columns (X,Y,Z,U,V). The X and Y columns have same
> length as factor1; and Z, U, and V have same length as factor2. Please see
> dataset is copied below. Please note that all dataset columns have NAs
> values.
> 
> *Need help on this:*
> 
> 
> Can we use the grubbs.test() function to detect all outliers and replace it
> by NA in X and Y datasets per group in factor1; and in Z, U, and V datasets
> per group in factor2. Columns in the dataframe have different lengths, but
> when I read the .csv file, R added NA values for the shorter columns.
> 
> If you need the .csv data file, please let me know.
> 
> 
> Thank you very much for your help in advance.
> 
> 
> 
> 
> install.packages("outliers")
> library(outliers)
> 
> datafortest<-read.csv("G:/data_for_test.csv", header=TRUE)
> datafortest
> 
> datafortest<-data.frame(datafortest)
> 
> datafortest$factor1<-as.factor(datafortest$factor1)
> datafortest$factor2<-as.factor(datafortest$factor2)
> 
> str(datafortest)
> 
> ##### tried to use grubbs.test() on a single column of the dataframe, but
> still not working
> tests.for.outliers.X<- grubbs.test(datafortest$X, na.rm = TRUE, type=11)
> 
> 
> ####################################
> 
> *grubbs.test() on a single dataset: but this can only detect if the min and
> the max are outliers.*
> 
> 
> xx999<-c(0.088,1,2,3,4,5,6,7,8,9,88,98,99)
> grubbs.test(xx999, type=11)
> 
> 
> 
> 
> With many thanks
> 
> Abou
> 
> 
> 
> factor1      X            Y         factor2          Z           U
>    V
> 1     4455.077 888 1 999           NA 999
> 1     4348.031 333 1 475            NA 240
> 1    9999.789 618 1 507 252 394
> 1    3813.139 417 1 603 332 265
> 1  7512.65 344 1 442 216           NA
> 1     5642.667            NA 1 486 217 275
> 1     6684.386 341 1 927 698 479
> 2     5165.731 999 1 971 311 562
> 2 NA 265 1 388 999 512
> 2     3259.241 557 2 888 444 777
> 2     3288.383 234 2 514            NA 322
> 2      1997.878 383 2 409 311           NA
> 2       99990.61           NA 2 546 327 728
> 2       2655.977          NA 2 523 228 653
> 3      3189.49 7777 2 313 456 450
> 3      1826.851 287 2 296 412 576
> 3      4386.002 352 2 320 251         NA
> 3      3295.091 308 2 388 888 396.5
> 3      2120.902 526 3 9999 398 888
> 3 NA 489 3 677 438 307
> 3      2056.123 291 3 555 428 219
> 3      1995.088 444 3              NA 319           NA
> 3 NA 349 3 479           NA 321
> 3      2539.873 333 3 257 406 417
>        3 313 334 409
>        3 296 465 546
>        3 320 180 523
>        3 388 999 313
> 
> 
> 
> ______________________
> 
> 
> *AbouEl-Makarim Aboueissa, PhD*
> 
> *Professor, Mathematics and Statistics*
> *Graduate Coordinator*
> 
> *Department of Mathematics and Statistics*
> *University of Southern Maine*
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
Hello,

With the data file you have attached I cannot reproduce any errors, all 
went well at the first try.


library(outliers)

fl <- "~/data_for_test.csv"
datafortest <- read.csv(fl)

# these are not needed to run the test
datafortest$factor1 <- as.factor(datafortest$factor1)
datafortest$factor2 <- as.factor(datafortest$factor2)
str(datafortest)
#> 'data.frame':    28 obs. of  7 variables:
#>  $ factor1: Factor w/ 3 levels "1","2","3": 1 1 1 1 1 1 1 2 2 2 ...
#>  $ X      : num  4455 4348 10000 3813 7513 ...
#>  $ Y      : int  888 333 618 417 344 NA 341 999 265 557 ...
#>  $ factor2: Factor w/ 3 levels "1","2","3": 1 1 1 1 1 1 1 1 1 2 ...
#>  $ Z      : int  999 475 507 603 442 486 927 971 388 888 ...
#>  $ U      : int  NA NA 252 332 216 217 698 311 999 444 ...
#>  $ V      : num  999 240 394 265 NA 275 479 562 512 777 ...
head(datafortest)
#>   factor1        X   Y factor2   Z   U   V
#> 1       1 4455.077 888       1 999  NA 999
#> 2       1 4348.031 333       1 475  NA 240
#> 3       1 9999.789 618       1 507 252 394
#> 4       1 3813.139 417       1 603 332 265
#> 5       1 7512.650 344       1 442 216  NA
#> 6       1 5642.667  NA       1 486 217 275

##### tried to use grubbs.test() on a single column of the dataframe, but
##### still not working
grubbs.test(datafortest$X, type = 11)
#>
#>  Grubbs test for two opposite outliers
#>
#> data:  datafortest$X
#> G = 4.6640014, U = 0.0091756, p-value = 0.02867
#> alternative hypothesis: 1826.851 and 99990.608 are outliers



Hope this helps,

Rui Barradas