similar to: Removing Outliers Function

Hi all, I'm trying to apply loess regression to my data and then use the fitted model to get the *standardized/studentized residuals. I understood that for linear regression (lm) there are functions to do that:* * * fit1 = lm(y~x) stdres.fit1 = rstandard(fit1) studres.fit1 = rstudent(fit1) I was wondering if there is an equally simple way to get the standardized/studentized residuals for a

Hola amigos, esta es mi primera duda, espero que no sea demasiado fácil. Tengo unos datos de dos variables y quiero mostrar recta de regresión y valor de correlación serie0 <- c(0.651, 0.712, 0.614, 0.645, 0.559, 0.647, 0.642, 0.534, 0.616, 0.621, 0.623) serie1 <- c(0.572, 0.641, 0.565, 0.596, 0.518, 0.604, 0.602, 0.501, 0.58, 0.589, 0.596) data <- cbind(serie0, serie1) colnames(data)

Dear list Getting very frustrated with this simple-looking problem > m1 <- lm(x~y, data=mydata) > outliers <- abs(stdres(m1))>2 > plot(x~y, data=mydata) I would like to plot a simple x,y scatter plot with labels giving custom information displayed for the outliers only, i.e. I would like to define a column mydata$labels for the mydata dataframe so that the command >

Hi, I wonder if anybody could help me in converting this easy SAS program into R. (I'm still trying to do that!) PROC IMPORT OUT= WORK.CHLA_italian DATAFILE= "C:\Documents and Settings\carleal\My Documents\REBECCA\stat\sas\All&nutrients.xls" DBMS=EXCEL2000 REPLACE; GETNAMES=YES; RUN; data chla_italian; set chla_italian;

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

Bueno, ya lo he solucionado gracias a Carlos me ha enviado un correo en privado (supongo que se ha despistado, si no lo querías hacer público ya es tarde) con esta info: -- Creo que lo tienes (en formato básico) aquí: https://stat.ethz.ch/pipermail/r-help/2007-November/146285.html Aunque pensaba que si tu objetivo último es el de que usuarios "potencialmente tontos" sean capaces de

Hi there, I hope I can get advice regarding the calculation of leverage values or studentized residual values of a non-linear regression model. It seems like rstudent() does not work on a nls object. Many thanks in advance! Best regards, Xingli

I am using the Unix version of R (version 1.7.0), installed via fink on a G4 Macintosh. I recently upgraded from version 1.6.0 and found that the "car" library now has a problem: ---Begin transcript--- >library(car) Attaching package 'car': The following object(s) are masked from package:base : dfbeta dfbeta.lm dfbetas dfbetas.lm hatvalues hatvalues.lm

I contacted John Fox about this first, because parts of the file are attributed to him. He says that he didn't write rstandard.glm(), and suggests asking r-devel. As it stands, rstandard.glm() has summary(model)$dispersion outside the sqrt(), while in rstandard.lm(), the sd is already sqrt()ed. This seems to follow stdres() in VR/MASS/R/stdres.R. Of course for the c("poisson",

Hi, I must be doing something silly here, because I can't get the studentised and standardised residuals from r output of a linear model to agree with what I think they should be from equation form. Thanks in advance, Jennifer x = seq(1,10) y = x + rnorm(10) mod = lm(y~x) rstandard(mod) residuals(mod)/(summary(mod)$sigma) rstudent(mod)

Dear community, I'm having this silly problem. I've a linear model. After fixing it, I wanted to know which data had studentized residuals larger than 3, so i tried this: d1 <- cooks.distance(lmmodel) r <- sqrt(abs(rstandard(lmmodel))) rstu <- abs(rstudent(lmmodel)) a <- cbind( mydata, d1, r,rstu) alargerthan3 <- a[rstu >3, ] And suddenly a[rstu >3, ] has

Hi, I am trying to figure out how to get the correlation coefficient for a QQ plot (residual plot). So to be more precise, I am creating the plot like this: qq.plot(rstudent(regrname), main = rformula, col=1) But want to also access (or compute) the correlation coefficient for that plot. Thanks, Tom [[alternative HTML version deleted]]

Sorry, I am sure, this must be documented somewhere (but there are that many docs and tutorials to scan for topics..., actually a great thing... but if you are in a hurry..): I want to save a plot as .ps (or .eps): > postscript("plot1.eps", horizontal=FALSE, onefile=FALSE,height=8,width=8,pointsize=10) > plot(hpfit$fit,rstudent(hpfit),xlab="Fitted

A colleague was asking me if R does multi-level modelling as opposed to multiple regression. Since I have no knowledge of multi-level modelling (except 5 minutes googling ) I thought that I would as here. Does are offer any multi-level modeling packages? It looked like arm might be one but I was not sure. Thanks

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]]

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 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 =

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.

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