search for: 95th

Any help with this problem would be greatly appreciated: I need to produce a custom plot i haven't come across in R. Basically, I want to show means, 1st standard deviation and 5th and 95th percentiles visually, using something resembling a boxplot. Is it possible to completely customize a boxplot so that it shows means as the bar (instead of, not as well as medians), standard deviations at the hinges (instead of IQR) and 5th & 95th percentiles at the brackets? The plotmeans funct...

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 bo...

Hi, How do I get R to output the 95% cutoff from a distribution of a continous variable? summary() only displays a few statistics.... Thanks!

...ch of doing a binary search when the previous binary search returned 0, and times for the new approach, which directly picks the first item/child node in the leaf/node. Current approach: Count: 5013 Range: 25.000 - 497.000; Mean: 82.767; Median: 64.000; Stddev: 49.972 Percentiles: 90th: 141.000; 95th: 182.000; 99th: 287.000 25.000 - 33.930: 211 ###### 33.930 - 45.927: 277 ######## 45.927 - 62.045: 1834 ##################################################### 62.045 - 83.699: 1203 ################################### 83.699 - 112.789: 609 ################## 112.789 - 151...

I have a 20x3 matrix as follows: > m <- replicate(3, matrix(rnorm(20),20,1)) I need to compute, say, 95th and 99th percentiles of each column such that the resulting matrix becomes 2x3 with each row representing the respective percentile. My "best effort" is to compute one column at a time as follows: > quantile(m[,1], c(0.95, 0.99)) To do the same for columns 2 and 3, I would simply ch...

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 "...

Hi, I'd like to move from excel to R because our dataset are so large. Here's what my data looks like: Transaction Rate Run# Transaction Type Location Latency in Seconds 10 1 Order A 0 10 1 Order B

Hi, Is it possible to produce box-and-whisker plots given that I have the median, interquartile and 5/95th centile values, but not the data from which they come? It seems that it ought to be possible to coerce bxp to do what I want, but I can't quite see how. Thanks, Matthew -- Matthew Vernon, Research Fellow Ecology and Epidemiology Group, University of Warwick http://blogs.warwick.ac.uk/mcverno...

The standard R boxplot appears to use quartiles to determine the height of the rectangles and a range parameter - RNG - (default=1.5 I think) that determines the length of the whiskers as <= RNG x Interquartile Range. Is it possible to instead define the range as extending to the 95th percentile? If so, how would this be done? nb, I'm plotting multiple boxplots on a single chart so a function that applies to multiple series would be useful. Thanks, Nick -------------- next part -------------- An HTML attachment was scrubbed... URL: https://stat.ethz.ch/pipermail/r-he...

Hi, I know some of you are very experienced as to the working of networks. I wondered whether there is some accepted way of determining bandwidth needs based on the network traffic over time. For example, looking at the figures for the network traffic through the server interface, we have hourly, daily and monthly figures. If everything were linear, taking the hourly figure and dividing it by

I would be grateful if members of the list could point me in the direction of any code (preferably in R) that will allow me to estimate 95th percentiles from a set of repeated measurements. For example, we are interested in a clinical measurement where we have 3 measures for 14 subjects and 2 measurements on 24 subjects and single measurement on 36 subjects. We want to combine these to form a Normal range by using something that takes a...

How do I calculate the 95th percentile when I know the 25th, the median and the 75th?? Thanks, Harmony Tenney [[alternative HTML version deleted]]

...ed. The problem is that with standard boxplots a too large number of observations are displayed as outliers. I also tried to display the log of the observations, but even then there are to may outliers to my taste. So I'd like to change the standard IQR box to a box which displays the 5th tothe 95th percentile instead of the standard 25th to 75th percentile. Is this possible and if so, how? I use both R and Splus, so I'd like to know for both flavours of S. Regards, Cornelis

I have distilled my bootstrap problem down to this bit of code, which calculates an estimate of the 95th percentile of 7500 random numbers drawn from a standard normal distribution: library(boot) per95 <- function( annual.data, b.index) { sample.data <- annual.data[b.index] return(quantile(sample.data,probs=c(0.95))) } m <- 10000 x <- rnorm(7500,0,1) B <- boot(data=x,statistic=per...

...2, type="l", ylim=c(0,1), xlab=xlab, axes=FALSE, ylab="Probability", las=1, main=titles[n]) axis(1) axis(2) lines(1:5, pred.mat[k+1,], lty=1) lines(1:5, pred.mat[k+2,], lty=3) legend("topright", c("avg. player", "5th %-tile player", "95th %-tile player"), lty=1:3, bty="n") n<-n+1 } } plotProb(q8.pred.mat.v13, c(193, 196, 199, 205, 217,241,289), c(3,3), q8.titles3, "identification") [1] "debug" [1] 193 [1] 1 [1] 1920 Error in print(pred.mat[k, ]) : error in evaluating the argument 'x...

...whether P(obs) is significantly higher than chance. I opted for a crude permutation approach: compute P(perm) over 10000 random permutations of Yobs (i.e., refit the multinom() model 10000 times randomly permuting Yobs) and consider P(obs) as significantly higher than chance if higher than the 95th percentile of the P(perm) distribution. Now, the problem is that the mode of P(perm) is always really close to P(obs), e.g., if P(obs)=1 (perfect discrimination) also the most likely P(perm) value is 1!!! I figured out that this is due to the fact that, with my data, randomly permuted classifi...

...ll PowerConnect 5224), four of my own servers (1U Opteron servers, single socket, dual core, dual NIC), as well 2 servers for 2 friends who will be subleasing from me. The package includes 6Mbps of bandwidth, burstable to 100Mbps. Bandwidth is tracked with 5-min samples, and as long as my 95th percentile is less than 6Mbps each month, there is no extra charge for bandwidth. I would like to use tc bandwidth shaping so that I can 1) ensure that I never have to pay for extra bandwidth in any month 2) be able to guarantee all servers a predefined minimum slice of bandwidth I am a softw...

Hello, I am synthesising some sales data over a twelve month period, and then trying to use the "predict" function, firstly to generate a thirteenth month forecast with upper and lower 95% confidence limits. So far so good But what I then want to do is add the upper sales value at the 95th confidence limit to the vector of thirteen months and their respective sales to create a fourteenth month with a predicted sale and the 95% upper confidence limit for this, and so on The idea being to create a "trumpet" of extreme posistions But I keep getting instead of one line of pre...

Hello, I have a question about using extreme value distribution in R. I have two variables, X and Y, and have pairs of points (X1,Y1),(X2,Y2), (X3,Y3) etc. When I plot X against Y, it looks like the maximum value of Y (for a particular X) is correlated with X. Indeed, when I bin the data by X-value into equally sized bins, and test whether the maximum value of Y for a bin is correlated with

Dear Contributors I would like to perform this operation using a loop, instead of repeating the same operation many times. The numbers from 1 to 4 related to different groups that are in the database and for which I have the same data. x<-c(1,3,7) datiP1 <- datiP[datiP$city ==1,x]; datiP2 <- datiP[datiP$city ==2,x]; datiP3 <- datiP[datiP$city ==3,x] datiP4 <-