similar to: More efficient matrix computation

When the binary search returns 0 (exact match), the target key will necessarily be at slot 0 of all nodes below the current one, so in this case the binary search is not needed because it will always return 0, and we waste time doing it, holding node locks for longer than necessary, etc. Below follow histograms with the times spent on the current approach of doing a binary search when the

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, 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

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

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

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

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

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.

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

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'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

I am looking to create what I would call a "simple variation" on the boxplot. What I would like to do is to be able to plot the upper and lower confidence limits as the "box" and the 10th and 90th percentile as the whiskers. What I have done is write the code to create a dataframe, the columns of which are the mean, sd, 10th percentile, 90th percentile, lower confidence limit

Hello, I have a doubt, but it is more statistic than just about R: How the people deal usually with negative percentile and quartile? In my concrete case, I want to know the distribution of an error, so the nearest it is to 0 the better (I think it would be optimun to have the nearest values to 0 in the lower percentiles). The best result would be making the percentile of the absolute value

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

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

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'd like to make boxplots of a large number of observations (+/- 20.000), which are distributed log-normal and right skewed. 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

I have been quantreg library for a number of projects but have just hit a snag. I am using nlrq to examine an asymptotic relationship between 2 variables at the 99th percentile. It performs as expected, however when I try to extract the coefficients along with se and significance I am running into problems. The problem is that for the nlrq regression Dat.nlrq, summary(Dat.nlrq) reports a different

Hi this is a very simple question ! if a have a set of date like x=c(1,2,3,4,4,5,6,8,7,8,8) how can I find out the percentile of 7 ? thanks Paolo

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