search for: iqr

Dear R users, Something is strange in summary and IQR. Suppose, I have a data set and I would like to find the Q1, Q2, Q3 and IQR. x<-c(2,4,11,12,13,15,31,31,37,47) > summary(x) Min. 1st Qu. Median Mean 3rd Qu. Max. 2.00 11.25 14.00 20.30 31.00 47.00 > IQR(x) [1] 19.75 However, I test the same data set in SAS &quo...

...n but I need the output to be in matrix with rownames and all the columns beside it this how I want it Col76 Col77 Min. : 7 39 1st Qu. : 1846 1630 Median : 3631 3376 Mean : 3804 3617 Sd : 3rd Qu.: 5772 5544 IQR : Max. : 7952 7779 Is there an easy way? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Summary-statistics-for-matrix-columns-tp4650489.html Sent from the R help mailing list archive at Nabble.com.

Hi all, I'm just getting started with R and I would appreciate some help. I'm having trouble creating a boxplot with whiskers at the 95th and 5th percentiles instead of at 1.5 * IQR. I have read the relevant documentation, and checked existing mails on this topic. I found a small modification that should work : https://stat.ethz.ch/pipermail/r-help/2001-November/016817.html and tried to implement it. Basically, it says to replace boxplot.stats with: myboxplot.stats <- fu...

Hi guys! I have to calculate the 95% CI for the IQR. I have 100samples with continuous numbers using a compute-intensive method. 1)I can calculate the 95%CI and the IQR, but I don't know how to calculate the CI of the IQR, does anybody have any idea, which method will be appropriate? 2)I have a 2x2 table with gender vs blue eyes or not. How do I...

This report follows the post http://tolstoy.newcastle.edu.au/R/e6/devel/09/03/0760.html where it is shown that quantile() and IQR() do not work as documented. In fact they do not check for numeric input even if the documentation says = : ?quantile x numeric vectors whose sample quantiles are wanted. Missing values are ignored. ?IQR x a numeric vector. > quantile(factor(1:9)) 0% 25% 50% 75% 100% 1 3...

Dear all, from the help page of quantile: "x ??? numeric vectors whose sample quantiles are wanted. Missing values are ignored." from the help page of IQR: "x ??? a numeric vector." as a matter of facts it seems that both quantile() and IQR() do not check for the presence of a numeric input. See the following: set.seed(11) x <- rbinom(n=11,size=2,prob=.5) x <- factor(x,ordered=TRUE) x ?[1] 1 0 1 0 0 2 0 1 2 0 0 Levels: 0 < 1 &lt...

...=================== my.boxplot.stats<-function (x, coef = 1.5, *type=6*, do.conf = TRUE, do.out = TRUE) { if (coef < 0) stop("'coef' must not be negative") nna <- !is.na(x) n <- sum(nna) stats <- stats::quantile(x, type=type,na.rm = TRUE) iqr <- diff(stats[c(2, 4)]) if (coef == 0) do.out <- FALSE else { out <- if (!is.na(iqr)) { x < (stats[2L] - coef * iqr) | x > (stats[4L] + coef * iqr) } else !is.finite(x) if (any(out[nna], na.rm = TRUE))...

...the legends for each chart leg_loc=matrix(c( -0.1, 0.26, 0.62, -0.1, 0.26, 0.4, 0.4, 0.4, 1, 1),ncol=2, nrow=5, byrow=FALSE) *Calculate the statistics for each sample size to display on the legends for (i in 1:5) { nR=(i-1)*500+1 nR2=nR+499 z=data[nR:nR2,13] m<-mean(z) std<-sqrt(var(z)) iqr=IQR(z) median=median(z) *Adding to the chart legend(leg_loc[i,1],leg_loc[i,2], legend= paste( "Mean=",round(m,3),'\n', "SD=",round(std,3),'\n', "Median =",round(median,3),'\n', "IQR=", round(iqr,3)),bty="n") } Do you know w...

That didn't work Jim! Thanks anyway On Mon, Apr 18, 2016 at 9:02 PM, Jim Lemon <drjimlemon at gmail.com> wrote: > Hi Michael, > At a guess, try this: > > iqr<-function(x) { > return(paste(round(quantile(x,0.25),0),round(quantile(x,0.75),0),sep="-") > } > > .col3_Range=iqr(datat$tenure) > > Jim > > > > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> > wrote: > > Hi, &gt...

Are you aware that there *already is* a function that does this? ?IQR (also your "function" iqr" is just a character string and would have to be parsed and evaluated to become a function. But this is a TERRIBLE way to do things in R as it completely circumvents R's central functional programming paradigm). Cheers, Bert Bert Gunter "The tr...

The following is from version 1.6.2 of R under Windows, or 1.6.1 under Mac OSX/X11 > density(1) Error in if (!(lo <- min(hi, IQR(x)/1.34))) (lo <- hi) || (lo <- abs(x[1])) || : missing value where logical needed I am not sure how this should be handled. I encountered it in connection with densityplot(). In that connection, it might be enough to modify density() so that it returns NA is these circumstances...

Dear list, I'm trying to implement the following function, but what I get is an error message and I don't understand where is the error: #outliers'identification: iqr=lapply(bb,function(){ inner_fencesl=quantile(x,0.25)-1.5*IQR(x) inner_fencesh=quantile(x,0.75)+1.5*IQR(x) outer_fencesl=quantile(x,0.25)-3*IQR(x) outer_fencesh=quantile(x,0.75)+3*IQR(x)}) where bb is a dataframe containing all the variables over wich the function must be applied. thanks of your att...

Again, IQR returns two both a .25 and a .75 value and it failed, which is why I didn't use it before. Also, the first function just returns tha same value repeating. Since they are the same, before the second call, using the mode function is just a way to grab one value. I could have used average, min, m...

??? IQR returns a single number. > IQR(rnorm(10)) [1] 1.090168 To your 2nd response: "I could have used average, min, max, they all would have returned the same thing., " I can only respond: huh?? Are all your values identical? You really need to provide a small reproducible example as req...

...the right edge of the box does not show the same 3rd Quartile as does ?summary.? Explain, please. > sort(t5g24times) [1] 111 135 201 234 283 283 284 285 300 370 387 496 > summary(t5g24times) Min. 1st Qu. Median Mean 3rd Qu. Max. 111.0 225.8 283.5 280.8 317.5 496.0 > iqr <- 317.5 - 225.8 > iqr [1] 91.7 > 317.5 + 1.5 * iqr [1] 455.05 > pdf() > boxplot(c(t5g24times), horizontal=1, range=1.5) R version info: platform x86_64-apple-darwin9.8.0 arch x86_64 os darwin9.8.0 system...

...ay how the suggestion did not work. Jim's function had a typo in it - was that the problem? Or did you not change the call to ddply to use that function. Here is something that might "work" for you: library(plyr) data <- data.frame(groupColumn=rep(1:5,1:5), col1=2^(0:14)) myIqr <- function(x) { paste(round(quantile(x,0.25),0),round(quantile(x,0.75),0),sep="-") } ddply(data, ~groupColumn, summarise, col1_myIqr=myIqr(col1), col1_IQR=stats::IQR(col1)) # groupColumn col1_myIqr col1_IQR #1 1 1-1 0 #2 2 2-4...

hi, i'm using /"boxplot()"/ to show some data: x <- c(0.99, 0.97, 0.91, 0.72, 1.00, 0.99, 1.02, 0.90, 0.91, 0.90, 1.02, 0.90, 1.35, 1.01, 0.92) boxplot(x) is it correct when i say: /"Boxes represent interquartile ranges (IQRs); bold horizontal lines, medians; whiskers, lowest and highest values still within 1.5 x IQR; open circles, outliers."? /thanks in advance for any help! cheers, tom human genetics, bern/ / [[alternative HTML version deleted]]

...a normal linear regression model and now I want to check for the residual normality assumption. If I check the distribution graphically and look at the descriptive characteristics (skewness and kurtosis are below 1), I would confirm that the residuals are normally distributed. > basicStats(IQR.in.mi02.nw.tdv.mix$residuals) round.ans..digits...6. nobs 19316.000000 NAs 0.000000 Minimum -0.639527 Maximum 0.693383 1. Quartile -0.083753 3. Quartile 0.088886 Mean...

Hi i am doing an environmental research The equation is as follow: gam(y1 ~ x1 + s(x2) + s(x3) + s(x4), family = gaussian, fit = true) I would like to obtain the beta coefficient and 95CI of x4 (or s(x4)), what should I do? Thanks, Lung -- View this message in context: http://r.789695.n4.nabble.com/mgcv-beta-coefficient-and-95-CI-tp3320491p3320491.html Sent from the R help mailing list

Well, instead of your functions try: Mode <- function(x) { tabx <- table(x) tabx[which.max(tabx)] } and use R's IQR function instead of yours. ... so I still don't get why you want to return a character string instead of a value for the IQR; and the mode of a sample defined as above is generally a bad estimator of the mode of the distribution. To say more than that would take me too far afield. Post on stat...