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$X, na.rm = TRUE, type=11)
####################################
*grubbs.test() on a single dataset: but this can only detect if the min and
the max are outliers.*
xx999<-c(0.088,1,2,3,4,5,6,7,8,9,88,98,99)
grubbs.test(xx999, type=11)
With many thanks
Abou
factor1 X Y factor2 Z U
V
1 4455.077 888 1 999 NA 999
1 4348.031 333 1 475 NA 240
1 9999.789 618 1 507 252 394
1 3813.139 417 1 603 332 265
1 7512.65 344 1 442 216 NA
1 5642.667 NA 1 486 217 275
1 6684.386 341 1 927 698 479
2 5165.731 999 1 971 311 562
2 NA 265 1 388 999 512
2 3259.241 557 2 888 444 777
2 3288.383 234 2 514 NA 322
2 1997.878 383 2 409 311 NA
2 99990.61 NA 2 546 327 728
2 2655.977 NA 2 523 228 653
3 3189.49 7777 2 313 456 450
3 1826.851 287 2 296 412 576
3 4386.002 352 2 320 251 NA
3 3295.091 308 2 388 888 396.5
3 2120.902 526 3 9999 398 888
3 NA 489 3 677 438 307
3 2056.123 291 3 555 428 219
3 1995.088 444 3 NA 319 NA
3 NA 349 3 479 NA 321
3 2539.873 333 3 257 406 417
3 313 334 409
3 296 465 546
3 320 180 523
3 388 999 313
______________________
*AbouEl-Makarim Aboueissa, PhD*
*Professor, Mathematics and Statistics*
*Graduate Coordinator*
*Department of Mathematics and Statistics*
*University of Southern Maine*
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Hello,
With the data file you have attached I cannot reproduce any errors, all
went well at the first try.
library(outliers)
fl <- "~/data_for_test.csv"
datafortest <- read.csv(fl)
# these are not needed to run the test
datafortest$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
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