similar to: panel.xyplot : incorrectly "connecting" points

R2.2, WinXP: I am using xyplot( ) to generate time plots of plasma concentration data. The following is an edited version of my code: xyplot(log.conc ~ time| group, data = foo, groups = subject, panel = function(x, y, panel.number, ...) { panel.superpose(x, y, subscripts = TRUE, groups = foo$group, type = 'l', col

R2.2 for WinXP, Splus 6.2.1 for HP 9000 Series, HP-UX 11.0. I am trying to get a handle on why the same lme( ) code gives such different answers. My output makes me wonder if the fact that the UNIX box is 64 bits is the reason. The estimated random effects are identical, but the fixed effects are very different. Here is my R code and output, with some columns and rows deleted for space

Hello RHelpers, This may already have been answered, but despite days of scouring through the archives I haven't found it. My goal is to add multiple fitted curves to a plot. An example data set (a data frame named df in following code) is: x1 y1 factor1 4 1298.25 0.00000000 1 5 1393.25 0.00000000 1 6 1471.50

Dear R users, I have a question regarding the use of xyplot in the lattice() package. I have two factors (each with two levels), and I??d like to change the order of the panels in a 2x2 panel layout from the default alphabetic order that R uses based on the names of the factor levels. My approach is (in principle) xyplot(y~x|Factor1+Factor2) Let??s assume, my factor levels for Factor1 are A

Hello list, I am dealing with a noisy function (gradient,hessian not available) with simple boundary constraints (x_i>0). I've tried constrOptim() using nelder mead to minimize it but it is way too slow and the returned results are not satisfying. simulated annealing is so hard to tune and it always crashes R program in my case. I wonder if there are any packages or functions can do

I apologize if this has been addressed before; recently I read an article in Forbes which discussed how SCO was going after companies that have been using Linux. The article made the point that the ideas behind GPL are under attack precisely because no one is making sure that the code being put into the freely avail. packages isn't owned by someone else. Here's my question: Is R

Hi everyone (again), before you all start screaming that the reordering of factors has been discusse on several threads and is not particular to ggplot2, hear me out. I can easily reorder my x-axis factor in facet.grid() in ggplot2. What I cannot reorder are the factors represented on the strips. I can see that the graphs are changing, so I am afraid of what it is I am doing. Why is ggplot2

Hi, # For publications, I am not allowed to repeat the axes. I have tried to remove the axes using: # yaxt="n", but it did not work. I have not understood how to do this in ggplot2. Can you help me? # I also do not want loads of space between the graphs (see below script with Dummy Data). # If I could make it look like the examples on the (nice) examples page: #

Often, when exploring a dataset, I'd like to plot several very different Y variables against the same X variable, in panels stacked one over the other. Is there an easy way to do this? I'd like to achieve an elegant look similar to the look achieved by lattice in conditioned plots--for instance no space between panels. But unlike in straightforward conditioned plot, each panel may be on a

Hi friends, I'm beginning in R and I have simple question. I have this piece of my program and how you see, that's ok (whit > num<- 0.002) num<-0.002 # ok, but not when I change whit num<-0... ? factor1<-1; while(1) { if (num*factor1<1) factor1<-factor1*10 else { print("out ok!!"); break; } } [1] "out ok!!" but when I change (whit >

Hello there, I have a situation where I would like to select the first row of a particular factor for a data frame (data example below). So that is, I would like to select the first entry when the factor1 =A and then the first row when factor1=B etc. I have thousands of entries so I need some general way of doing this. I have a minimal example that should illustrate what I am trying to do. I am

Dear all, I use a nested design with lm and glm, with factor2 nested within factor1. In order to test for the significance of both factors, I use anova tables on the obtained models such as follows: /> mod1<-lm(A~factor1/factor2) > amod1<-anova(mod1, test="F") Analysis of Variance Table Response: A Df Sum Sq Mean Sq F value Pr(>F) factor1

Is names(model1$coef) what you're looking for? -----Original Message----- From: Kenneth Cabrera [mailto:krcabrer at epm.net.co] Sent: 29 November 2002 10:36 Cc: R-help at stat.math.ethz.ch Subject: [R] Obtaining the variable names of a glm object Hi, R users! Suppose I make a model like this:

I have a question that must have a simple answer (but eludes me). I need a row-by-row logical comparison across three numeric variables in a data frame: foo$x, foo$y, foo$z. The logic is if( x < y || x > z ) 1 else 0 for a particular row. It is simple and very inefficient to use for(i in 1:length(foo$x)){ } loops. How can I accomplish this using sappy( ) / lapply( ) / apply( ) or

Dear R people, I have a couple of questions about post-doc analyses for 2 by 2 within subjects ANOVA. I conducted a psycholinguistic study that combined a 2 by 2 design and a latin square design. Specifically, I had 32 items each of which generated 4 conditions. Participants saw each of the 32 items only once: 8 in Condition A, 8 in B, 8 in C, and 8 in D. The table below serves as an example.

Dear R users, I posted a couple of questions and got no response, so I am giving it another shot. I ran an experiment with a TWO-WAY within subject design. A sample dataset is in http://www-scf.usc.edu/~hex/data.txt I already ran ANOVA by using the following formula: aov(RT~Factor1*Factor2 + Error(Subject/(Factor1*Factor2)), data=data) and I obtained the following information: -------------

Full_Name: Tanya Logvinenko Version: 1.7.0 OS: Windows 2000 Submission from: (NULL) (132.183.156.125) For unbalanced design, I ran into problem with ANOVA (aov function). The sum of squares for only for the second factor and total are computed correctly, but sum of squares for the first factor is computed incorreclty. Changing order of factors in the formula changes the ANOVA table. For the

Hi All, I have a 4-dimensional data. I'm using barchart() function from lattice package. The R code and data are below - code includes one for stack=TRUE and other for stack=FALSE. I would like to present the data in another form which would be plotting Factor3 levels (P, Q, R, S) as two stacked bars (side by side). Like, for each level of Factor1 there should be two bars: first bar showing

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

Hi All, I'm trying to format the y-axis in an xyplot to show numbers with a comma separating the thousands but I'm not able to do it using formatNum(y, big.mark=","). This is what I have: library(lattice) year<-c(2003,2004,2005,2006,2007,2008,2003,2004,2005,2006,2007,2008)