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How to replace the outliers with 5th and 95th percentile values in R?
There are many ways to define an outlying value and it can be manually set by the researchers as well as technicians. Also, we can use 5th percentile for the lower outlier and the 95th percentile for the upper outlier. For this purpose, we can use squish function of scales package as shown in the below examples.
Example1
library(scales) x1<−1:10 x1<−squish(x1,quantile(x1,c(.05,0.95))) x1
Output
[1] 1.45 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 9.55
Example2
x2<−c(−5,rnorm(78),5) x2
Output
[1] −5.00000000 −0.39993096 −0.11249038 1.06589235 1.17195813 0.15677178 [7] −0.08325310 0.57986817 −0.05529031 0.13352083 1.00608625 −0.86860404 [13] 0.53672576 −0.15262216 −0.81247587 −0.31263625 −1.51127713 −1.59689010 [19] −0.11242962 −1.08234352 −0.04935398 −0.65185804 −1.10369370 0.68732306 [25] 1.83448401 1.08689945 −1.20674408 −1.25753553 0.03354570 0.67981025 [31] 0.24871123 −1.49969111 1.19287825 1.04406030 −1.31756416 0.10204579 [37] 1.48272096 0.97661717 0.50006441 −1.36247153 0.99895292 −0.49534106 [43] −0.24105508 0.35006991 −2.16041158 −1.12644863 2.23190981 −0.51413222 [49] 0.03760280 −1.12237961 −1.54094088 −0.37365780 0.02138277 1.97702046 [55] 0.37190626 −0.59456892 −0.06652980 −1.04453387 −0.50884324 0.85025142 [61] −0.66718350 −0.69703588 0.44922344 0.64238500 −1.11403189 0.66251032 [67] 0.79601219 −0.74801795 −0.10957126 −0.90781918 −2.13721781 1.43186180 [73] −0.32571115 −0.97929747 1.10822193 0.94719910 0.58934102 −1.29942407 [79] 3.83469537 5.00000000
Example
x2<−squish(x2,quantile(x2,c(.05,0.95))) x2
Output
[1] −1.54373835 −0.39993096 −0.11249038 1.06589235 1.17195813 0.15677178 [7] −0.08325310 0.57986817 −0.05529031 0.13352083 1.00608625 −0.86860404 [13] 0.53672576 −0.15262216 −0.81247587 −0.31263625 −1.51127713 −1.54373835 [19] −0.11242962 −1.08234352 −0.04935398 −0.65185804 −1.10369370 0.68732306 [25] 1.83448401 1.08689945 −1.20674408 −1.25753553 0.03354570 0.67981025 [31] 0.24871123 −1.49969111 1.19287825 1.04406030 −1.31756416 0.10204579 [37] 1.48272096 0.97661717 0.50006441 −1.36247153 0.99895292 −0.49534106 [43] −0.24105508 0.35006991 −1.54373835 −1.12644863 1.84161083 −0.51413222 [49] 0.03760280 −1.12237961 −1.54094088 −0.37365780 0.02138277 1.84161083 [55] 0.37190626 −0.59456892 −0.06652980 −1.04453387 −0.50884324 0.85025142 [61] −0.66718350 −0.69703588 0.44922344 0.64238500 −1.11403189 0.66251032 [67] 0.79601219 −0.74801795 −0.10957126 −0.90781918 −1.54373835 1.43186180 [73] −0.32571115 −0.97929747 1.10822193 0.94719910 0.58934102 −1.29942407 [79] 1.84161083 1.84161083
Example3
x3<−c(-50,rpois(198,5),50) x3
Output
[1] −50 5 4 8 6 2 1 6 3 5 7 7 8 5 8 8 5 8 [19] 3 2 3 0 5 6 2 6 6 2 7 5 9 4 5 3 9 7 [37] 4 3 6 5 2 4 9 5 7 1 2 4 2 3 5 5 6 1 [55] 5 7 1 9 6 3 5 4 3 9 5 4 6 8 4 4 6 4 [73] 5 2 4 5 5 7 8 6 3 5 8 5 8 5 2 5 2 8 [91] 6 6 5 7 2 2 5 5 4 3 5 3 7 2 4 6 8 6 [109] 3 4 9 2 2 2 4 4 6 6 5 5 3 5 3 6 6 4 [127] 6 4 4 5 9 6 2 1 3 8 5 7 5 6 6 5 7 2 [145] 8 8 6 5 3 4 5 10 6 6 3 6 2 7 7 5 8 7 [163] 7 3 4 8 4 4 6 8 3 6 4 10 4 3 5 4 4 5 [181] 4 5 4 5 4 5 6 8 2 5 12 12 3 6 5 4 4 5 [199] 5 50
Example
x3<−squish(x3,quantile(x3,c(.05,0.95))) x3
Output
[1] 2 5 4 8 6 2 2 6 3 5 7 7 8 5 8 8 5 8 3 2 3 2 5 6 2 6 6 2 7 5 9 4 5 3 9 7 4 [38] 3 6 5 2 4 9 5 7 2 2 4 2 3 5 5 6 2 5 7 2 9 6 3 5 4 3 9 5 4 6 8 4 4 6 4 5 2 [75] 4 5 5 7 8 6 3 5 8 5 8 5 2 5 2 8 6 6 5 7 2 2 5 5 4 3 5 3 7 2 4 6 8 6 3 4 9 [112] 2 2 2 4 4 6 6 5 5 3 5 3 6 6 4 6 4 4 5 9 6 2 2 3 8 5 7 5 6 6 5 7 2 8 8 6 5 [149] 3 4 5 9 6 6 3 6 2 7 7 5 8 7 7 3 4 8 4 4 6 8 3 6 4 9 4 3 5 4 4 5 4 5 4 5 4 [186] 5 6 8 2 5 9 9 3 6 5 4 4 5 5 9
Example4
x4<−c(−50,rexp(48,3.1),50) x4
Output
[1] −50.00000000 0.46067329 0.15298747 0.22637363 0.23424447 [6] 0.15467335 0.37455989 0.07762013 0.33175821 0.09303333 [11] 0.03806199 0.20649621 0.22883480 0.49089164 0.82497712 [16] 0.04780089 0.05156566 0.35638257 0.37319578 0.71100713 [21] 0.08649528 0.31543159 0.02263685 0.00963146 0.44814049 [26] 0.34506738 0.29533295 0.13803055 0.05497129 0.03901786 [31] 0.01818446 0.78122217 0.04863415 0.33353520 0.39530353 [36] 0.05385106 0.19991695 0.16913554 0.01549729 0.15901185 [41] 0.65120205 0.36483214 0.18226180 0.20708671 0.01590697 [46] 1.01257680 0.42223292 0.17291614 0.15793390 50.00000000
Example
x4<−squish(x4,quantile(x4,c(.05,0.95))) x4
Output
[1] 0.01568165 0.46067329 0.15298747 0.22637363 0.23424447 0.15467335 [7] 0.37455989 0.07762013 0.33175821 0.09303333 0.03806199 0.20649621 [13] 0.22883480 0.49089164 0.80528739 0.04780089 0.05156566 0.35638257 [19] 0.37319578 0.71100713 0.08649528 0.31543159 0.02263685 0.01568165 [25] 0.44814049 0.34506738 0.29533295 0.13803055 0.05497129 0.03901786 [31] 0.01818446 0.78122217 0.04863415 0.33353520 0.39530353 0.05385106 [37] 0.19991695 0.16913554 0.01568165 0.15901185 0.65120205 0.36483214 [43] 0.18226180 0.20708671 0.01590697 0.80528739 0.42223292 0.17291614 [49] 0.15793390 0.80528739
Updated on: 08-Feb-2021
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