similar to: new to R, analysis of latency data

Dear List, I am trying to solve a problem by the neural network method(library: nnet). The problem is to express Weight in terms of Age , Sex and Height for twenty people. The data frame consists of 20 observations with four variables: Sex, Age, Height and Weight. Sex is treated as a factor, Age and Weight are variables normalized to unity, as usual. I wanted to construct a neural network, and so

Hello list, after somes days I have this error when I run git pull in samba4 error: Unable to find 3b6a88a1a49fdc23cd956c6583e9ec56e541eeae under http://gitweb.samba.org/samba.git Cannot obtain needed blob 3b6a88a1a49fdc23cd956c6583e9ec56e541eeae while processing commit 1a596076697624545f415eb558c4647267cfe46c. error: Fetch failed. root at jupiter:/home/run# error: Unable to find

Hi I am having some problems running a covariate analysis with my colleage using R with the NonMem program we are using for a graduate school project. R and NonMem run fine without adding in the covariates, but the program is giving us a problem when the covariate analysis is added. We think the problem is with the R code to run the covariate data analysis. We have the control stream, R code

Colleagues, I have written an R function (see fully annotated code below), with which I want to process a dataframe within levels of the variable StepType. My program works, it processes the data within levels of StepType, but the usual headers that separate the output by levels of StepType are at the end of the listing rather than being used as separators, i.e. I get Regression results StepType

Hello Zed ! I''ve experimented a simple but limited performance tweak in the mongrel rails loader. With the following apache 2.2 mod proxy loadbalancer setup : # Redirect all non-static requests to cluster RewriteCond %{DOCUMENT_ROOT}/%{REQUEST_FILENAME} !-f RewriteRule ^/(.*)$ balancer://mongrel_cluster%{REQUEST_URI} [P,QSA,L] We can assume that mongrel is called only when the

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

Dear Group, I have the following dataset: ID REPI DV CONC SS 1 1 156.84 116 0 1 2 146.56 116 0 1 3 115.13 116 0 1 4 207.81 116 0 1 5 129.53 116 0 1 6 151.48 116 0 1 7 158.95 116 0 1 8 192.37 116 0 1 9 32.97 116 0 1 10 151.66 116 0 I want to calculate the percentile of each CONC within ID=i and add as a column

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

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

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,

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

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

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 folks, I'm trying to estimate bias-corrected percentile (BCP) confidence intervals on a vector from a simple for loop used for resampling. I am attempting to follow steps in Manly, B. 1998. Randomization, bootstrap and monte carlo methods in biology. 2nd edition., p. 48. PDF of the approach/steps should be available here: https://wyocoopunit.box.com/s/9vm4vgmbx5h7um809bvg6u7wr392v6i9 If

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

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

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 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

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 <-

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