similar to: Prevent sequential repeated values in data frame column

Hi, This is really strange. Can anyone help explain what's going on here (on 3 and 7)? > targets <- seq(from=.1, to=.9, by=.1) > targets[1]==.1 [1] TRUE > targets[2]==.2 [1] TRUE > targets[3]==.3 [1] FALSE > targets[4]==.4 [1] TRUE > targets[5]==.5 [1] TRUE > targets[6]==.6 [1] TRUE > targets[7]==.7 [1] FALSE > targets[8]==.8 [1] TRUE >

Hi, I often use plotmeans() from the gplots package to quickly visualize a pattern of change. I would like to be able to plot separate lines for different groups, but the function gives an error when a grouping variable is included in the formula argument. For instance, > require(gplots) > x <- data.frame(Score=rnorm(100), Time=rep(1:10, 10),

Hi, There is an object, ".Last.value" to which the result of the most recent evaluation is assigned. This is similar to "ans" in Matlab. In Matlab "ans" can be very useful and time-saving, but typing the larger R version is somewhat clunky and takes away from the usefulness. Is it possible to reassign '.Last.value' to something simpler, like

Hi, I want to add error bars to a plot generated with xyplot. I've tried both errbar() and plotCI(), but in both cases the points are not in the same place. It's as if the two functions are using a different frame of reference for the plotting area. for example: means <- c(92.5, 92.25, 90.9, 91.0, 94.15, 90.05) #means time <- c(1,1,2,2,3,3) #occasion variable group <-

Hello, I am confused about the order of nesting in mixed models using functions like aov(), lme(), lmer(). I have the following data: n subjects in either condition A or B each subject tested at each of 3 numerical values ("distance" = 40,50,60), repeated 4 times for each of the 3 numerical values ("trial" = 1,2,3,4) Variable summary: Condition: 2 level factor Distance:

Hi, I've looked all over for a solution to this, but haven't had much look in specifying what I want to do with appropriate search terms. Thus I'm turning to R-help. In the process of trying to write a simple function to rename individual column names in a data frame, I ran into the following problem: When I rename the columns within my function, I can't seem to get it to

Hi, I've done my best to search for a solution to this, but had no luck. How can I create a lattice plot (I'm using xyplot() ) that does not have a border on the top and right side, but keeps the bottom/left axes? So far all I've found is this, which inserted into the xyplot call removes all 4 borders: / par.settings = list(axis.line = list(col = 0))/ xyplot( Sepal.Length ~

Hello, I make frequent use of the *step()* and, for plotting, *all.effects() *functions for *lm()* objects. I am now doing more with *lme()* random effects models, and haven't been able to find functions similar to *step()* or *all.effects()* which will accept *lme()* objects. Do similar functions for either exist? If someone could point me in the right direction it would be much

Hi, I'm having some problems with the aggregate() function in the {stats} package, and the documentation doesn't address them. 1) Why would the first line work, but the second not? According to the help file, it accepts a "data=" argument. > with(tsrc, aggregate(x=DistRatio, by=list(Condition), FUN=mean)) Group.1 x 1 Congruent 1.741789 2 Mismatch 1.771425

Hi there, Could somebody help me disect this legacy R script I inherited at work, I have two questions: 1. I've tried to upgrade our R version from 1.6.2 (yeah, I know), to R 2.0, but some of the lines in this script are not compatible with R 2.0, could someone help me figure out where the problem is? 2. the jpeg generated (attached) seems to be off on some of the data, is there a better way

Hello, How can I label a secondary axis in R? At the moment it's labelled as c(-100,200). Obviously I would like it to be more sensible. Here is the code I am using newx = -100+37.5*((1:9)-1) axis(4,at=newx,labels=(newx+100)/3750) Thanks, Rob -- View this message in context: http://www.nabble.com/Labelling-a-secondary-axis-in-R-tp16807708p16807708.html Sent from the R help mailing list

Hello everyone I'm a beginner in Stats and R, I'm using R 2.10.1. I need to create a multivariate qq plot, there is 8 variable group with each has 55 number of input. An example of what I did so far, just to get my point out: > data=read.csv(file.choose(),header=T) > data country village group av_expen P2ary_ed no_fisher 1 Cook Islands Aitutaki D

I have a classification tree model similar to the following (slightly simplified here): > treemod<-tree(y~x) where y is a factor and x is a matrix of numeric predictors. They have dimensions: > length(y) [1] 1163 > dim(x) [1] 1163 75 I?ve evaluated the tree model and am happy with the fit. I also have a matrix of cases that I want to use the tree model to classify. Call it

Could someone please suggest a more clever solution to the following problem than my loop below? Given X a 2xN matrix X, and I a k-subset of N, Generate the (2^k)xN matrix Y with columns not in I all zero and the other columns with all choices of an entry from the first or second row of X. For example, with X <- matrix(1:8, nrow=2) I <- c(1,3) X is 1 3 5 7 2 4 6 8 and Y should be 1 0 5

I'd like to compare two models which were fitted using gls, however I'm having trouble interpreting the results of gls. If any of you could offer me some advice, I'd greatly appreciate it. Short explanation of models: These two models have the same fixed-effects structure (two independent, linear effects), and differ only in that the second model includes a corExp structure for

Dear all with image I can plot only one set of values in one plot. Do somebody have any insight how to put those 2 matrices into one picture so that in one cell in image picture are both values from mat[1,1] and mat2[1,1]. mat<-matrix(1:4, 2,2) mat2<-matrix(4:1,2,2) x <-1:2 y <-1:2 image(x, y, mat) image(x, y, mat2) The only way I found is to mix x or y for both matrices let

Hi, I am trying to simulate animal movement in a gridded landscape made up of cells. At each time step (iteration), the animal moves from one cell to another in a random fashion. This is how I am simulating movement, where a and b are the x,y co-ordinates of the animal at the previous time step: for (i in 1:no.of.steps){ direction <- sample(1:8, 1) if(direction == 1){ a <- a b <- b -

I think that the "dimname names" of tables and arrays could make aperm() and apply() (and probably some other functions) easier to use. (dimname names are, for example, created by table() ) The use would be something like: -- x <-table( from=sample(3,100,rep=T), to=sample(5,100,rep=T)) trans <- x / apply(x,"from",sum) y <- aperm( trans,

I am fitting a regression model with a bs term and then making predictions based on the model. According to some info on the internet at http://www.stat.auckland.ac.nz/~yee/smartpred/DummiesGuide.txt there are some problems with using predict.lm when you have a model with terms such as bs,ns,or poly. However when I used one of the examples they said would illustrate the problems I get virtually

Dear friends, I need to fill in (duplicate the whole record) the missing days with the same record values as long as AE is the same value (i.e. "1"), once AE value changes, the process of duplication should proceed with the new AE value till it changes again. e.g. I need to fill in records: day 18-day 44, all the records are carried with the new AE value of "0". At the