search for: mymeans

I'm using R-2.6.2 on Fedora Linux 9. I've been experimenting with plotmath. I wish it were easier to combine expressions in plotmath with values from the R program itself. There are two parameters in the following example, the mean "mymean" and standard deviation "mystd". I am able to use bquote to write elements into the graph title like mu = mymean and R will

Dear All, I have a database of 200 observations named myD. In the dataframe there are a column named code (with codes varying from 1 to 77), a column named "prevalence" with some quantitative measurements are given and an column named Pr_mean, with no values. I would like to set a cycle to compute the average of prevalence values for each different code and store the averages under the

Hi, this is a made-up example. Function "myfun" returns two arguments. Can "apply" be used so that "myfun" is called only once? Thanks Serguei mat<-matrix(runif(50),nrow=10,ncol=5) myfun<-function(x) { mymean<-mean(x) mysd<-sd(x) return(mymean,mysd) } out1<-t(apply(mat,1,function(x) myfun(x)$mymean)) out2<-t(apply(mat,1,function(x)

Hi all, I have two very large samples of data (10000+ data points) and would like to perform normality tests on it. I know that p < .05 means that a data set is considered as not normal with any of the two tests. I am also aware that large samples tend to lead more likely to normal results (Andy Field, 2005). I have a few questions to ensure that I am using them right. 1) The Shapiro-Wilk

Dear R users, My set-up: OS=Windows XP, R-2.9.2, Rtools210 I faced the follwing problem with the package compilation: There is no "/inst" or "/etc" subdirectory in the package-zip-file. And the content of the "/etc" subdirectory is lost, too. I tried a simplified "test" package. The "test" package has the following structure (see also attachement:

I am trying to plot the mean and standard error of three separate conditions. For various reasons, I do not have access to the raw data from which the mean and error were derived and would like to make error bar plots utilizing only the actual mean and standard error values. Is there a way to do this in R? Thanks for any help in advance. james [[alternative HTML version deleted]]

I have a dataframe ("mydf") that contains "differences of means". I wish to test whether these differences are significantly different from zero. Below, I calculate the t-statistic for each column. What is a "good" method to calculate/look-up the p-value for each column? mydf=data.frame(a=c(1,-22,3,-4),b=c(5,-6,-7,9)) mymean=mean(mydf) mysd=sd(mydf)

Dear R-users, please consider the following minimal example: \documentclass[a4paper,titlepage,onecolumn,12pt]{article} \usepackage[italian]{babel} \usepackage{amssymb} \usepackage[utf8x]{inputenc} \usepackage[pdftex]{graphicx} \begin{document} <<label=test, echo=FALSE, results=tex>>= df.data1 <- cbind.data.frame(A = rnorm(18), B =factor(rep(LETTERS[1:6],

R programming question, not machine learning, although that's the content. Apologies to all for whom the following code is eye-burning. I am using foreach() to run a simulation on a randomForest model (actually conditional randomForest ... "party" package). The simulation is in two dimensions. examining how "mtry" and "ntrees" are related in terms of predictive

What in the world am I missing?? > x<-rnorm(20) > mean(x) [1] -0.2272851 > results<-boot(x,mean,R=5) > results[2] $t [,1] [1,] -0.2294562 [2,] -0.2294562 [3,] -0.2294562 [4,] -0.2294562 [5,] -0.2294562 Jeff Morris Ortho-Clinical Diagnostics A Johnson & Johnson Co. Rochester, NY Tel: (585) 453-5794 [[alternative HTML version deleted]]

Hi, I've read in a csv file (test.csv) which gives me the following table: Hin1 Hin2 Hin3 Hin4 Hin5 Hin6 HAI1 9534.83 4001.74 157.16 3736.93 484.60 59.25 HAI2 13272.48 1519.88 36.35 33.64 46.68 82.11 HAI3 12587.71 5686.94 656.62 572.29 351.60 136.91 HAI4 15240.81 10031.57 426.73 275.29 561.30 302.38 HAI5 15878.32 10517.14 18.93 22.00 16.91

Hello, I need to plot the means of some outcome for two groups (control vs intervention) over time (discrete) on the same plot, for various subsets such as gender and grade level. What I have been doing is creating all possible subsets first, using the aggregate function to create the means over time, then plotting the means over time (as a simple line plot with both control & intervention

I quoted the relevant part of the documentation for you. Have you actually try to read what it says? Sure, you don't get any error, but have you checked whether any bootstrapping was actually done? Most of those functions are generics, thus having the "..." argument that can take anything. Doesn't mean they will be used. See if the following helps: > x <- 1:10 >

Hi, I am trying to create a power curve to show how the power of a t-test varies depending on the mean. Any ideas how I should go about this? Louisa _________________________________________________________________ [[alternative HTML version deleted]]

I am trying to calculate monthly means by year of phosphates and nitrates from a multi year data set. Can anybody help me out with the most effective way to do this? My data looks like this: Collection_Date                   Test.Name              Value 2000-01-24 17:00:00            Phosphate               0.108 2000-01-24 17:00:00            Nitrate                     0.037 2001-11-12

Hello, does anyone know how to take the mean for a subset of observations? For example, suppose my data looks like this: OBS NAME SCORE 1 Tom 92 2 Tom 88 3 Tom 56 4 James 85 5 James 75 6 James 32 7 Dawn 56 8 Dawn 91 9 Clara 95 10 Clara 84 Is there a way to get

Hi everyone, I have dataset which I make a sample of it couple of times and each time I get the mean and standard deviation of each row for each sample. I have a function for that, which takes the name of the file and number of times to sample and then returns the mean and standard deviation for each row in each sample. Sample=function(name, n){

Kia Ora > vec_size(data.frame(x = 1:10)) > #> [1] 10 > vec_size(array(dim = c(10, 4, 1))) > #> [1] 10 I think that "length" (in the R way) or "size" should incorporate the number of columns (or other dimension information). How about: > vec_npoints (x) > vec_nrecords (x) > vec_nobs (x) Depending on whether you want to promote geometry, databases

Is there a way to set "na.rm=TRUE" as a default, so that this does not have to be re-specified for all of the functions requiring this option? Thanks in advance, Stephanie Broyles sbroyl@lsuhsc.edu [[alternative HTML version deleted]]

Hi I am really new using R, so this is really a beginner stuff! I created a very small data set on excel and then converted it to .csv file. I am able to open the data on R using the command "read.table ("mydata1.csv", sep=",", header=T)" and it just works fine. But when I want to work on the data (e.g. calculate the mean of variable "X") R says