similar to: detection of outliers

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

Hello, I d like to run a survival analysis with "left truncated data". Could you recommend me a package to do this please ? Thanks Philippe Guardiola ________________________________________________________________________ Re?evez AOL Mail sur votre t?l?phone. Vos e-mails accessibles ? tout moment! Cr?ez un e-mail gratuit aujourd?hui.

Dear R users I m planning to move to Linux to use R (currently under Win XPPro on a 32bit PC with 4 Go RAM), I have 2 questions: - is there a recommended "version/distribution" of Linux to run?R and Bioconductor packages: Fedora ? Ubuntu ? Suse ? Debian ? - Regarding Fedora, I see that now it is version 8 available on the web, but on R website I can only see R Fedora 7 version (no F8);

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]]

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

Hi, I am new to R and I would like to get your help in finding 'outliers'. I have mvoutlier package installed in my system and added the package . But I not able find a function from 'mvoutlier' package which will identify 'outliers'. This is the sample list of data I have got which has one out-lier. 11489 11008 11873 80000000 9558 8645 8024 8371 It will

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 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

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 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, 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

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

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

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

Tu fichero tiene los decimales como puntos y no como comas como tu le indicas. Te dejo un ejemplo #--------------------------------------------------------------------------------------------------------------------- setwd(dir="c:/Users/usuario/Desktop/") library(outliers) filename<-"timediff.csv" time<-read.csv(filename, sep=";",header=TRUE,dec=".")

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

Hola buenos días, ahora mismo estaba haciendo una función para quitar outlier por condición. Pero lo cierto es que aunque la función consigue quitarlos creo que me ha quedad bastante farragoso. Os dejo el codigo y si me dais algún consejo para mejorarlo mejor que mejor. Mcuhas gracias #############################################################• # Ojo este script puede instalarte librerias que

Hola Marta, si observas cualquier artículo de psicología esto es una práctica típica. Te digo psicología porque creo que tus datos son de ese tipo. Tienes bibiligrafía de artículos cientificos en las que se quitan valores siguiendo los criterios que te he dicho solo has de buscar bibliografía del campo en el que te mueces. Osea que nos quitarlos por que sí, aunque en cada area de ciencia tienes