similar to: z-score to percentile, and back again (Normal)

I will have a blind student in my AP Statistics class this year. I'm thinking about using R as his calculator. It seems like it's core text-in text-out nature may match screen reading software well. And I'd like to explore directing visualizations to tactile graphics output. I'm wondering if anyone could give me suggestions (people, websites, organizations) where I could discover

I have a problem where I need to calculate the corresponding cohort percentile ranks for each of several variables. Essentially, what I need is a function that will calculate the distribution-free percentiles from each variable's data vector, returning a corresponding vector of percentiles: e.g.: percentile.my.data<-/function/(my.data) I tried to make ecdf() perform this task but

Hi, Is there a function that does percentile-percentile plot. I do not mean the qqplot. I need to plot the percentiles rather than points themselves. I am hoping for a plot that tells me that the x percentile of one data set corresponds to the y percentile of the other. for example a point on the plot of (.5, .2) will tell me that the 50th percentile of the first data and the 20th percentile of

Hi all, I have a problem on how R calculates Percentiles : Suppose I have following data set: > data1 [1] -16648185 -14463457 -14449400 -13905309 -13443436 -13234755 -12956282 -11660896 [9] -10061040 -9805005 -9789583 -9754642 -9562164 -9391709 -9212182 -9151073 [17] -9092732 -9068214 -8978151 -8943912 -8761890 -8632106 -8541580 -8501249 [25] -8234466 -8219015

Dear list, I am calculating the 95th percentile of a set of values with R and with SPSS In R: > normal200<-rnorm(200,0,1) > qnorm(0.95,mean=mean(normal200),sd=sd(normal200),lower.tail =TRUE) [1] 1.84191 In SPSS, if I use the same 200 values and select Analyze -> Descriptive Statistics -> Frequencies and under "Statistics", I type in '95' under Percentiles,

Dear List, I have some discrete data and want to calculate the percentiles and the percentile ranks for each of the unique scores. I can calculate the percentiles with quantile(). I know that "ecdf" can be used to calculate the empirical cumulative distribution. However, I don't know how to exact the cumulative probabilities for each unique element. The requirement is similar

Has anyone developed a defensible method of estimating percentiles from a univariate kernel density estimate? I am working on a problem in which the density estimate is of interest, but I would also like to estimate the value of the variable for which the distribution was, say, 0.20. I spent some time searching the archives and found some message from 2006 that implied such a method was not

Hello all, Thanks in advance for you attention. I would like to generate a third value that represents the quantile value of a variable in a data frame. # generating data x <- as.matrix(seq(1:30)) y <- as.matrix(rnorm(30, 20, 7)) tmp1 <- cbind(x,y) dat <- as.data.frame(tmp1) colnames(dat) <- c("id", "score") dat # finding percentiles of "score"

I was hoping to calculate the percentile for each date. So group all of one date together, calculating the value of the 2.5 and 97.5 percentile. -- View this message in context: http://r.789695.n4.nabble.com/Calculating-percentiles-for-multiple-dates-tp4638183p4638378.html Sent from the R help mailing list archive at Nabble.com.

Is there an R function that inputs a value and a vector, and returns the percentile corresponding to the value? Something like pvalue<-function(x,vector){mean(x>=vector)} but with interpolation. Given the above function, is there a way to do the following without the loop: for(i in 1:10) y[i] <- pvalue(x[i],vector) where x and y are numeric vectors of length 10? -- Art Salwin

Hi, can anyone help me to figure out how to compute the percentile of an individual observation with respect to a reference distribution. What I mean is. Let's assume I have a vector consisting of 10 numbers {3,5,8,1,9,5,4,3,5.5,7} and I want figure out what percentile the number 4.9 corresponds to. I failed to find any reference to such a function, although I would assume this must

Hi, I am using the package "demography" from Rob Hyndman for the Lee-Carter-Model. It is an amazing powerful tool but I am struggling with one issue: I want to compute different percentiles of the survival probability distribution derived from the Lee-Carter-Forecast (e.g. the 50%tile, 60%tile, 75%tile and 99%tile) for each of the next 10 years. Is there any possibility to retrieve

Dear List, I have a two-part question related to bpplot(), a box-percentile plot function in the Hmisc package. Take the example given in the Help for bpplot(), for instance. (1) How does one set but not draw the y-axis? What I did was, bpplot(... , yaxt="n"), but that apparently does not work (though it works for boxplot()). (2) How does one display the mean value of each variable

Hi all, One quick question: How to put values of 25 and 75 percentile on boxplot? Thanks in advance. Nianqing Xiao, Ph.D NCI Center for Bioinformatics, NIH SAIC/Advanced Systems Group > 6116 EXECUTIVE BLVD 4026J > MSC 8335 > BETHESDA MD 20852 Phone: 301-451-6357 Fax: 301-480-4222 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list --

Hi All: I am working with a dataset on Arsenic toxicity, and I am trying to calculate the 20th, 40th, 60th, 80th, and highest percentiles for a variable, dietary Moisture (variable name dMoist). The inbuilt function quantile(dMoist) would print 0, 25th, 50th, 75th, and 100th percentile. Does there exist a function that can calculate xth percentile (where x = 10th, 20th, ... etc) values?

Hello I need to calculate and insert the values for the 50,75,90,95 & 99 percentiles in a data frame for each row. I used agr1$quantile <- quantile(agr1$cnt, probs=c(.50, .75, .90, .95, .99)) but that didn't work. How can calculate the percentile for my variable "cnt" , insert & name the percentile as p50, p75, etc in my data frame agr1? Thanks in advance for your

Hi there! Still struggling to translate Matlab code into R's tsDyn package. Here is my question: Is there in R an equivalent function to Matlab's prctile()? To the moment I thought it was quantile(), but I just realized I was wrong. The definition of the Matlab function: prctile Percentiles of a sample SyntaxY = prctile(X,p) Description Y = prctile(X,p) calculates a value that is

Hi All, I am looking at applications of percentiles to time sequenced data. I had just been using the quantile function to get percentiles over various periods, but am more interested in if there is an accepted (and/or R-implemented) method to apply weighting to the data so as to weigh recent data more heavily. I wrote the following function, but it seems quite inefficient, and not really very

Dear R users, I came up to a problem dealing with percentiles in R. >From my previous questions: I do have a big data.frame, with lots of columns and rows. The following command enables me to calculate means for all data frame. dat1$newID<-rep(1:(nrow(dat1)/12),each=12) #if nrow(dat1)/12 is integer dat2<-with(dat1,aggregate(cbind(dat1[,1:71]),by=list(newID),mean)) What I need is to

Hello, I'm trying to get percentiles (PERCENTRANK for excel users) by factor in the following data.frame: myExample <- data.frame(Ret=seq(-2, 2.5, by=0.5),PE=seq(10,19),Sectors=rep(c("Financial","Industrial"),5)) myExample <- na.omit(myExample) Thanks to Patrick I I managed to put together the following lines which does it for the "Ret" column: myecdf