similar to: image plot with multiple x values

I am helping my wife do some statistical analysis. She is a biologist, and she has performed some measurements on various genotypes of mice. My background is in applied mathematics and engineering, and I have a fairly good statistics background, but I am by no means a PhD level expert in statistical methods. We have used the lmer package to fit various models for the various experiments that she

Dear R list, I'm having difficulties in choosing between a list or a data.frame, or an array for the storage and manipulation of my data (example follows). I've been using the three for different purposes but I would rather like to know which is more adapted to what task. Here is the data I'm currently working on: 200 observations, each observation being a vector of length

Hi evrybody, in a matrix consisting of 49 columns, I would like to plot all columns against the first in 48 different graphs. Can you help me? Thank you in advance Sebastian -- *************************************************************************************************************** Dipl. Biol. Sebastian Krug PhD - student IFM - GEOMAR Leibniz Institute of Marine Sciences Research

Hello R list, I have two matrices of identical dimensions, and I want to fit a straight line for each pair of columns and plot the resulting lines. I got it to work with a for loop, but there must be a better way, > n<-5 > N<-10 > > data.x<-matrix(1:(n*N),ncol=n) > data.y<-matrix(1:(n*N) + rnorm(n*N,sd=1),ncol=n) > >

I have executed a Repeated Measures ANOVA with one DV (latency) and one within subject factor (acoustic condtion: 3 levels) by bootstrapping my sampling distribution of F from the empirical sample distribution. I chose to resample because the sample distribution deviates from normality a lot. The overall F is significant and now I wish to decompose this with contrasts to ask if latencies to

[Yes, this is related to a homework problem, but is not the problems itself.] In my mathematical statistics class, we've just learned about properties of estimators, and I can now solve manually problems like this: A sample of size n = 16 is drawn from a normal distribution where sigma = 10 but mu is unknown. If mu = 20, what is the probability that the estimator mu hat = Y bar will lie

Please note clarifications in <<>> below. My apologies for any confusion. Thanks again, Scott ---------- Forwarded message ---------- From: Scott Stark <stark.sc@gmail.com> Date: Aug 23, 2007 1:03 PM Subject: Expedite scalar f(x) evaluation over vectors To: r-help@lists.r-project.org Dear R community, I am trying to code a fairly complex equation for optim(). My current

Hi! I'm translating some code from Matlab to R and I found a problem. I need to translate Matlab's function 'lsqnonlin' (http://www-ccs.ucsd.edu/matlab/toolbox/optim/lsqnonlin.html) into R, and at the beginning I thought it would be the same as R's 'optim'. But then I looked at the definition of 'lsqnonlin' and I don't quite see how to make

I have a server that runs stand-alone with an LDAP directory and a KDC . The linux machines have sssd to allow unified users etc. The clients are mostly MacOS and Windows machines that aren't part of an AD. This config has worked for 15 years, but after upgrading Debian and bringing in Samba Version 4.17.7-Debian it seems to be broken. I believe this is related to:

Folks, I wonder if anything could be said about the distribution of a random variate x, where x = N(0,1)/N(0,1) Obviously x is pathological because it could be 0/0. If we exclude this point, so the set is {x/(0/0)}, does x have a well defined distribution? or does it exist a distribution that approximates x. (The case could be generalized of course to N(mu1, sigma1)/N(mu2, sigma2) and one

Dear All, Is there any package to do multi-objective optimization? For instance, consider the following problem: maximize f(x,y) in order to x and maximize g(x,y) in order to y, simultaneously, with x and y being the same both for f and g. Can R do it numerically? Thanks in advance, Paul

Hello, I've been trying to use ggplot, but I cannot seem to get my data in the correct form. I usually have a vector x, and a matrix y and I would usually use matplot(x,y) to plot the columns of y against x. Now, if i understand correctly, I should cast x and y into a data.frame and do something like ggplot(x,y,data=data). I think I'm missing something here: do I really need to

I am a SAS user currently evaluating R as a possible addition or even replacement for SAS. The difficulty I have come across straight away is R's apparent difficulty in handling relatively large data files. Whilst I would not expect it to handle datasets with millions of records, I still really need to be able to work with dataset with 100,000+ records and 100+ variables. Yet, when reading

Dear R helpers, I'm trying to write a numerical scheme for a boundary integral method to solve an electromagnetic problem. This requires the computation of the distance between points at the surface of an object (a sphere, in my example). Here is my code, > require(rgl) > r<-1 > size<-10 > theta<-seq(0,2*pi,length=size*2) > phi<-seq(0,pi,length=size) > pc

Hello: I am using R mainly on windows XP, version 2.5. I?m a biologist, with a medium level statistics background. I have a problem stating a two-way factorial design where both factors are random. I?m using the lmer() function implemented in the Matrix package version 0.99. My design is as follows: Two species were randomly selected from a total of 4 species. This species are present

I have 316 files. Each file represents a patient's breathing track (respiratory signal recorded for a variable number of cycles). All files have the same are made up of a header followed by a variable number of records. Each record contains 7 comma separated fields. The patient ID is recorder in the header which is stripped off when reading the file into a R data.frame. Since I need to keep

Dear list useRs, I have to generate a random set of coordinates (x,y) in [-1 ; 1]^2 for say, N points. At each of these points is drawn a circle (later on, an ellipse) of random size, as in: > N <- 100 > > positions <- matrix(rnorm(2 * N, mean = 0 , sd= 0.5), nrow=N) > sizes<-rnorm(N, mean = 0 , sd= 1) > plot(positions,type="p",cex=sizes) My problem is to

Dear All, I know how to export graphics as pdf files and then how to include them in LaTeX documents. However, I do not know how to do in order to have the text of the graphics written with the font selected for the LaTeX document. Is that possible? Thanks in advance, Paul

I'm looking for a function in R similar to t.test() which was generously pointed out to me yesterday, but which can be used for normally distributed data. To recap yesterday: > x <- scan() 1: 62 52 68 23 34 45 27 42 83 56 40 12: Read 11 items > alpha<- .05 > t.test(x) One Sample t-test data: x t = 8.8696, df = 10, p-value = 4.717e-06 alternative hypothesis: true

Dear All, Consider a matrix (N x N) where each entry is either zero or one (can hardly get any simpler). Now, I would like to plot it as a 'chessboard' where every matrix entry is a black (1) or white (0) square. Whatever tool I use to plot it, it should not try to interpolate the data at all. I found some online references http://www.phaget4.org/R/image_matrix.html but probably I can