similar to: How to put values of 25 and 75 percentile on boxplot?

Hi all, Is there a convenient way to calculate Spearman correlation coefficients in R? Nick 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 -- Read

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

Heeeelp Given this data x <- c(1,5,100,300,250,200,550,900,1000) > quantile(x) 0% 25% 50% 75% 100% 1 100 250 550 1000 When I run the quantile, I can only know the value of the nth percentile I want to know what's the percentile position of each items in the list Sample 1 = 100% on the list has 1 or more 5 = more than x% on the list has 5 or more 100 = more than x% on the

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, 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

hello; firstly, my gratitude to all who help me to find a function that allows me to add confidence interval to my graph. in order to calculate the (1-alpha)th percentile of for exemple an F(df1,df2) distribution i do like this: v<-df(alpha,df1,df2) percentile<-qf(v,df1,df2,alpha) if it is true please alert me , and if it is not what should do then? :handshake: -- View this message in

Dear All, I have to get the value of say 90th percentile of precipitation time series.. The series is of daily precipitation value of 96 years, I have to to get 90the percentile value of daily precipitation each year. If you know the R code or command for this please let me know. I would appreciate your early response. Thanking you, Sincerely, Ajay.

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

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

Dear Nabble. I am trying to draw a box percentile plot with trellis using the panel in Hmisc. I really want to colour the plots in. I can alter several of features of the plot by changing the trellis par settings but I just can’t fill the shape in. Here is some example code which alters line colour and dot symbol: require(lattice) require(Hmisc)

Dear all, I am familiar with obtaining the value corresponding to a chosen probability via the quantile function. Now I am facing the opposite problem I have a value an want to know it's corresponding percentile in the distribution. So is there a function for this as well? Thank you for your support in advance, Felix

Hi: I have an array of measurements, that I've been doing linear regression model and AI models on. Because there are many errors and the values are "ill-formed" I would like to copy the array, but replace each value with the PERCENTILE of that value, in the original array. i.e. mesments$V1: 9, 77, -1 would become: mesmentsCopy$V1: 50, 100, 0 The actual array has many more

To calculate Percentile for a set of observations Excel has percentile() function. R function quantile() does the same thing. Is there any significant difference btw percentile and quantile? Regrads, -- View this message in context: http://www.nabble.com/Diff-btw-percentile-and-quantile-tp22328375p22328375.html Sent from the R help mailing list archive at Nabble.com.

In R, what is the best way to convert z-scores (Normal distribution) to a percentiles, and vice-versa. (I'll be looking to do the same with other distributions eventually.) === Peter Petto <ppetto at ppetto.com> Bay Village, OH 440.249.4289

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,

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

Hi- I wanted percentage labels on a qqnorm x axis. I used the following: #make up some data jt<-rnorm(100) #qqnorm with percentile x labels qqnorm(jt,axes=F,xlab="Percentiles") box() l<-c(1,5,10,30,50,70,90,95,99) axis(1,at=qnorm(l/100),label=l) which was ok for this data set. Does anyone have a more general solution which would allow one to specify the number of x labels

Hello, I am not sure how to do this in R. Any suggestion would be appreciated. I have a vector of values from where I build an empirical CDF. For example: > x <- seq(1,100) > x <- sample(x,1000,replace=T) > quantile(x,probs=seq(0,1,.05)) 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 1.00 5.00 10.00 16.00 20.00 25.00 31.00 36.00 41.00

Hi, all dear R experts, I am really stuck by how to get the 5th percentile( with a 95% CI )of the Kaplan-meier estimator of survival function P(T>t). I have a simulated sample of lifetime Ts, then I set the KM estimator < km.fit<-survfit(Surv(T),type="kaplan-meier",data=Surv(T)) <quantile(km.fit,.05) However, it gave "Error in order...". Does someone have some

I'm familiar with the quantile() command, but what if I have a specific number that I want to know its location in a vector? I know that in known distributions, (for example the normal distribution), there is pnorm and qnorm, but how can I do it with unknown vector? thanks in advance _________________________________________________________________ Walla! Mail - [1]Get