similar to: xyplot() groups scope issue

Hi all, I understand that it is simple to create data with a specific correlation (say, .5) using mvrnorm from the MASS library: > library(MASS) > set.seed(1) > > a=mvrnorm( + n=10 + ,mu=rep(0,2) + ,Sigma=matrix(c(1,.5,.5,1),2,2) + ,empirical=T + ) > a [,1] [,2] [1,] -1.0008380 -1.233467875 [2,] -0.1588633 -0.003410001 [3,] 1.2054727 -0.620558768

Hi all, Hopefully this will be quick, I'm looking for pointers to packages/ functions that would allow me to calculate the power of a t.test when the DV has measurement error. That is, I understand that, ceteris paribus, experiments using measure with more error (lower reliability) will have lower power. Mike -- Mike Lawrence Graduate Student, Department of Psychology, Dalhousie

Hi all, I have collected response time data from 178 participants ('sub') for each combination of 4 within-Ss factors ('con','int','tone','cue'). Additionally, I have recorded the gender of each participant, so this forms a between-Ss factor ('gender'). Normally this would be analyzed using aov:

Hi all, A suggestion derived from discussions amongst a number of R users in my research group: set the default column names produced by aggregate () equal to the names of the objects in the list passed to the 'by' object. ex. it is annoying to type with( my.data ,aggregate( my.dv ,list( one.iv = one.iv ,another.iv = another.iv ,yet.another.iv = yet.another.iv )

You could calculate the confidence interval of the correlation at your desired df: http://davidmlane.com/hyperstat/B8544.html The below code takes as arguments the observed correlation, N, and alpha, calculates the confidence interval and checks whether this includes 0. cor.test2=function(r,n,a=.05){ phi=function(x){ log((1+x)/(1-x))/2 } inv.phi=function(x){

Hi all, This is my first post to the developers list. As I understand it, aggregate() currently repeats a function across cells in a dataframe but is only able to handle functions with single value returns. Aggregate() also lacks the ability to retain the names given to the returned value. I've created an agg() function (pasted below) that is apparently backwards compatible (i.e.

Hi all, Just thought I'd share something I discovered last night. I was interested in creating animations consisting of a series of plots and after finding very little in the usual sources regarding animation in R directly, and disliking the imagemagick method described here (http://tolstoy.newcastle.edu.au/R/help/05/10/13297.html), I discovered that if one exports the plots to a

Hi all, Consider the following function: #### my.func = function(x){ y=ifelse(x>-.5,0,ifelse(x< -.8,abs(x)/2,abs(x))) print(c(x,y)) #print what was tested and what the result is return(y) } curve(my.func,from=-1,1) #### When I attempt to find the maximum of this function, which should be -.8, I find that optimize gets stuck in the plateau area and doesn't bother testing the

Hi all, Looking to calculate the expected mean and variance of a ratio distribution where the source distributions are gaussian with known parameters and sample values are correlated. I see (from wikipedia: http://en.wikipedia.org/wiki/ Ratio_distribution#Gaussian_ratio_distribution) that this calculation is quite involved, so I'm hoping that someone has already coded a function to

Hi all, I'm using the code below within a loop that I run thousands of times and even with the super-computing resources at my disposal this is just too slow. The snippet below takes about 10s on my machines, which is an order of magnitude or two slower than would be preferable; in the end I'd like to set the number of monte carlo experiments to 1e4 or even 1e5 to ensure stable

Hi all, By default a call to xyplot from the Lattice package when using 2 factors [eg xyplot( dv~iv | XY * AB ) ] yields the following shingle structure: |_A_|_A_|_B_|_B_| |_X_|_Y_|_X_|_Y_| However, I'm wondering if it is possible to merge the upper shingle within levels of that factor, as in: |___A___|___B___| |_X_|_Y_|_X_|_Y_| Mike -- Mike Lawrence Graduate Student, Department of

Hi all, I'm having a problem with the auto.key function in xyplot. I hate to bother the list like this and I'm positive I must be missing something very simple, yet I've spent the last day searching for a solution to no avail. Essentially, I want a key that contains entries in which the plot points are superimposed on a line of the same color as the points, like this: o--o--o Now,

Hi all, Worked & looked around for a while on this to no avail. I'm trying to create a plotmath expression that achieves: ?i >> 0 and while: expression(Delta*i>0) comes close, I'd prefer to have the >> (denoting "very much greater than"). Maybe >> is a non-standard expression and therefore not supported? Mike -- Mike Lawrence Graduate

I'm looking to analyze a large data set: a within-Ss 2*2*1500 design with 20 Ss. However, aov() gives me an error, reproducible as follows: id = factor(1:20) a = factor(1:2) b = factor(1:2) d = factor(1:1500) temp = expand.grid(id=id, a=a, b=b, d=d) temp$y = rnorm(length(temp[, 1])) #generate some random DV data this_aov = aov( y~a*b*d+Error(id/(a*b*d)) , data=temp ) While yields the

Hi all, I'm looking for an analytic method to obtain the PDF & CDF of the sampling distribution of a given correlation (rho) at a given sample size (N). I've attached code describing a monte carlo method of achieving this, and while it is relatively fast, an analytic solution would obviously be optimal. get.cors <- function(i, x, y, N){ end=i*N

Has anyone successfully compiled pnmath (http://www.stat.uiowa.edu/~luke/R/experimental ) for an intel processor running mac OS 10.5? When I attempt to do so via the R package installer (choosing "Local Source Package" and pointing to the pnmath_0.0-2.tar.gz file), I get the following errors: * Installing *source* package 'pnmath' ... ** libs ** arch - i386 gcc -arch i386

Hi all, I'm trying to plot error bars in a lattice plot generated with xyplot. Deepayan Sarkar has provided a very useful solution for simple circumstances (https://stat.ethz.ch/pipermail/r-help/2005-October/081571.html), yet I am having trouble getting it to work when the "groups" setting is enabled in xyplot (i.e. multiple lines). To illustrate this, consider the singer data

Hi all, I am extremely newbie to R. Can anybody jump-start me with any clues as to how do I get a cumulative histogram from two independent variables, cumhist(X,Y) ? -jose [[alternative HTML version deleted]]

Hello, i'm trying to find a more modern system to reproduce the functionality that was available through the Histoscope program (from Fermilab). Namely, the capability of connecting to a running process and having plots update in realtime in response to new data. Is this possible with R? Thank you, Charles Cosse [[alternative HTML version deleted]]

Hello everyone, A little background first: I have collected psychophysical data from 12 participants, and each participant's data is represented as a scatter plot (Percieved roughness versus Physical roughness). I would like to know whether, on average, this data is best fit by a linear function or by a quadratic function. (we have a priori reasons to expect a quadratic) Some of my