similar to: how to find outliers from the list of values

Hello all, I am estimating parameters for regression functions on experimental data. Functional response of Rogers type II. I would like to know which points of my dataset are outliers. What is the best method to do this with R? I found a method via R help, but would like to know if there are better methods for my purpose. Here is the script I us now: library("mvoutlier") dat

I haven't seen this cryptic warning before: > update.views('Robust') Warning message: In update.views("Robust") : The following packages are not available: covRobust, distr, FRB, MASS, mblm, multinomRob, mvoutlier, quantreg, RandVar, rgam, RobAStBase, robfilter, RobLox, RobRex, robust, RobustAFT, robustbase, ROptEst, ROptRegTS, rrcov, sandwich, wle >

Hi All, I am working on the dataset in which some of the variables have more than one observations with outliers . I am using below mentioned sample script library(outliers) x1 <- c(10, 10, 11, 12, 13, 14, 14, 10, 11, 13, 12, 13, 10, 19, 18, 17, 10099, 10099, 10098) outlier_tf1 = outlier(x1,logical=TRUE) find_outlier1 = which(outlier_tf1==TRUE, arr.ind=TRUE) beh_input_ro1 =

Suppose I am reading data from a file and the data contains some outliers. I want to know if it is possible in R to automatically detect outliers in a dataset and remove them -- View this message in context: http://n4.nabble.com/How-to-detect-and-exclude-outliers-in-R-tp1017285p1017285.html Sent from the R help mailing list archive at Nabble.com.

Happy holidays all! I know it's very subjective to determine whether some data is outlier or not... But are there reasonally good and realistic methods of identifying outliers in R? Thanks a lot! [[alternative HTML version deleted]]

Last week there was a thread on outlier detection. I came across an article which has a very interesting paragraph. The article is Missing Values, Outliers, Robust Statistics, & Non-parametric Methods by Shaun Burke, RHM Techology Ltd, High Wycombe, Buckinghamshire, UK. It was the fourth article in a series which appeared in Scientific Data Management in 1998 and 1998. The very

Hi All- I have 24 boxplots on one graph. I do not have the whiskers extending to the outliers, but I would like to label the maximum value of each outlier above the whiskers. I have the stats but am having trouble figuring out how to label the whiskers. Any suggestions would be great! sherri

Dear R-users, I have two outliers related questions. I. I have a vector consisting of 69 values. mean = 0.00086 SD = 0.02152 The shape of EDA graphics (boxplots, density plots) is heavily distorted due to outliers. How to define the interval for outliers exception? Is <2SD - mean + 2SD> interval a correct approach? Or should I define 95% (or 99%) limit of agreement for data interval,

Hi, this is both a statistical and a R question... what would the best way / test to detect an outlier value among a series of 10 to 30 values ? for instance if we have the following dataset: 10,11,12,15,20,22,25,30,500 I d like to have a way to identify the last data as an outlier (only one direction). One way would be to calculate abs(mean - median) and if elevated (to what extent ?) delete the

Hi everybody, I'd like to know if there's an easy way for extracting outliers record from a dataset, in order to perform further analysis on them. Thanks Alessandro

Hello, I'm seeking ideas on how to remove outliers from a non-normal distribution predictor variable. We wish to reset points deemed outliers to a truncated value that is less extreme. (I've seen many posts requesting outlier removal systems. It seems like most of the replies center around "why do you want to remove them", "you shouldn't remove them", "it

Hi everybody, I am wondering how i can add a "stretch" color bar / legend to a graph that uses colorBrewer to define the colors in it. I will try to explain my graph, but i also uploaded it at: ftp://ftpext.usgs.gov/pub/er/fl/st.petersburg/Monica_pal/ The file is: robcor_training_pca.pdf - i will also attach this file in case some people accept attachments. So i took apart the

Dear List and Hadley, I would like to have a boxplot with ggplot2 and have the outlier values labelled with their "name" attribute. So I did > library(ggplot2) > dat=data.frame(num=rep(1,20), val=c(runif(18),3,3.5), name=letters[1:20]) > p=ggplot(dat, aes(y=val, x=num))+geom_boxplot(outlier.size=4, outlier.colour="green") >

Hello all, I have a question: I am using the interquantile method to spot outliers & it gives me values of say 234 & -120 or for the higher & lower benchmarks. I don't have any issues w/ the higher end. However I don't have any negative values. My lowest possible value is 0. Should I consider 0 as an outlier? Thanks ahead for your thoughts -- View this message in

dear all, could somebody tell me how I can plot mild outliers as a circle(?) and extreme outliers as an asterisk(*) in a box-whisker plot? Thanks very much in advance -- View this message in context: http://www.nabble.com/mild-and-extreme-outliers-in-boxplot-tp25040545p25040545.html Sent from the R help mailing list archive at Nabble.com.

Dear list, I'm forwarding these 2 messages as suggested by the package developer. My system is > sessionInfo() R version 2.9.0 (2009-04-17) i486-pc-linux-gnu on Ubuntu 8.04, with r-base-core, r-base-dev and r-recommended installed from binaries through Synaptic. I normally install the rest of packages using install.packages() from within R (started from an xterminal by su) Agus

Dear experts, I am a beginner of R. I'm looking for experts to guide me how to do programming in R in order to randomly replace 5 observations in X explanatory variable with outliers drawn from U(15,20) in sample size n=100. The replacement subject to y < 15. The ultimate goal of my study is to compare the std of y with and without the presence of outliers based on average of 1000

Hello all, I wrote a small function to add labels for outliers in a boxplot. This function will only work on a simple boxplot/formula command (e.g: something like boxplot(y~x)). Code + example follows in this e-mail. I'd be happy for any suggestions on how to improve this code, for example: - Handle boxplot.matrix (which shouldn't be too hard to do) - Handle cases of complex

Hello, I've been searching for a method for identify outliers for quite some time now. The complication is that I cannot assume that my data is normally distributed nor symmetrical (i.e. some distributions might have one longer tail) so I have not been able to find any good tests. The Walsh's Test (http://www.statistics4u.info/ fundsta...liertest.html#), as I understand assumes that the

This is my a part of my data set > D[1:15,c(1,5:10)] X. media IE.2005 IE.2006 IE.2007 IE.2008 IE.2009 IE.2010 1 1108 22.00000 60.0 39 4.0 8.0 16.0 5.0 2 1479 110.00000 NA NA 53.0 1166.0 344.8 110.0 3 1591 86.60000 247.0 87 95.0 94.0 81.0 76.0 4 3408 807.00000 302.0 322 621.0 1071.0 1301.0 1225.0