similar to: An array of an array of boxplots in lattice

Dear sir or ma'am, I have a question about the dataset "fgl." The dataset seems to be in the "VR" package, so I tried to download it from CRAN. However, after downloading, when I tried to load the package, it was not in my package list. I am wondering what is wrong. Any advice on how to access the fgl dataset would be appreciated. Thanks. Seungho Huh

Dear R users: I have a continuous outcome variable and four predictors, two continuous and two dichotomous. i would like to use the lattice plot to create scatter plots for the continuous predictors and boxplots for the dichotomous predictors. with 4 continuous variables, this is what i have been doing: trial = rbind ( cbind ( cimt$ant.mean, cimt$age, 1 ), cbind ( cimt$ant.mean, cimt$sbp, 2 ),

Hi All, I need a small help with following code: I'm trying to convert "dashed lines" to regular ones; and changing default "blue" border color to say "black"... but I'm doing it wrong and its not working. Can anyone help please. Thanks, Code: require(lattice) ex <- data.frame(x=1:10, y=rep(c("A","B"), 5)) bwplot(y~x, data=ex,

I'm very new to R, so please forgive me if I just missed the answer in existing documentation... I have a data set with at least three columns, X, Y, and Z. I want to produce a chart where one axis shows all the unique values of X, and the other axis shows all the unique values of Y. Each cell within the chart should contain the result of applying an aggregate function (such as mean(), for

Dear List-Members, I would like to produce a ordered boxplot in which the categories with the smallest median are plotted at the left end and the box with the largest median at the right. Thanks in advance for any advices Thomas H.

Hi all, Can anyone who is familar with CART tell me what I missed in my tree code? library (MASS) myfit <- tree (y ~ x1 + x2 + x3 + x4 ) # tree.screens () # useless plot(myfit); text (myfit, all= TRUE, cex=0.5, pretty=0) # tile.tree (myfit, fgl$type) # useless # close.screen (all= TRUE) # useless My current tree plot resulted from above code shows as:

Hi, I am trying to make a multi-class classification tree by using rpart. I used MASS package'd data: fgl to test and it works well. However, when I used my small-sampled data as below, the program seems to take forever. I am not sure if it is due to slowness or there is something wrong with my codes or data manipulation. Please be advised ! The data is described as the output from str()

> From: Peter Dalgaard BSA <p.dalgaard@biostat.ku.dk> > > Martin Maechler <maechler@stat.math.ethz.ch> writes: > > > Reading the long output of ``cc -flags'', > > I see that more than average optimization is done using > > cc -xO[1-4] > > # And -O is -xO2. If you do want higher speed, you need to use other flags too, and -fast is a

Say I have x = seq(1, 40) y = seq(1, 40)^2 g = rep(c("A", "B", "A", "B"), each = 10) xyplot(y~x, groups = g, type = 'l') Is there a way to have a single line and have it be one color when g == "A", and another when g == "B"? Thanks! Regards, Andrew Liu Fixed Income | Investment Fellow T. Rowe Price 100 E. Pratt St, BA-0735

Hi All, I'm familiar with bwplot() in lattice package. Is it possible to get such a boxplot using lattice package: http://www.reading.ac.uk/ssc/publications/graphics/mma-fig1.gif instead of the following default: http://media.wiley.com/wires/WICS/WICS22/mfig005.gif My aim is to get a compact boxplot for publication. Having legend can help because otherwise x-axis labels are repeated for

Dear R-users, dear Prof. Ripley as package maintainer I tried to investigate the odd error, when I call nnet together with a 'weights' parameter, using the 'fgl' example in V&R p 348 The error I get is: Error in eval(expr, envir, enclos) : Object "w" not found I think it is a kind of scoping problem, but I really cannot see, what the problem exactly is. and

Hello list members, I am working with simulated data for landscape pattern analysis. I have 1000 replicates of binary (2 colour) gridded landscapes at each combination of 9 levels of class proportion and 11 levels of spatial autocorrelation. The results are stored in an array as follows: > dim(surfaces) [1] 38 9 11 1000 The dimensions are defined as follows: [x,,,] 1:38, integers

Dear all, I'm having a few problems trying to reshape a data frame. I tried with reshape{stats} and melt{reshape} but I was missing something. Any help is very welcome. Please find details below: ################################# # data in its original shape: indiv <- rep(c("A","B"),c(10,10)) level.1 <- rpois(20, lambda=3) covar.1 <- rlnorm(20, 3, 1) level.2

I am using lattice to make figures as pdfs: trellis.device(device = "pdf",file = "Figure6.pdf",color = FALSE) I need to specify some blank space on the left-hand margins (the pages will be bound so we need about 0.5 inch)). I have tried a number of solutions but none seems to work (e.g. par.set). Can this be done when initiating the plotting device? Or is the some other way

Dear R users, I want to do discriminant analysis on my data. I have successfully followed the discriminant analysis in V & R on the iris data: > ir <- rbind (iris3[,,1],iris3[,,2],iris3[,,3]) > ir.species <- c(rep("s",50),rep("c",50),rep("v",50)) > a <- lda(log(ir),ir.species) > a$svd^2/sum(a$svd^2) [1] 0.996498601 0.003501399 > a.x <-

I am very new to R so forgive me if this seems basic but I have done extensive searching and failed to come up with the answer for myself. I am trying to label a boxplot I have created with the values for the median, upper and lower quartiles and max and min values. I have been unable to do this or find anything on the net to say how it might be done. Is this possible and if so how? Regards,

I have a data frame of ~200 columns and ~20,000 rows where each column consists of binary responses (0,1) and a 9 for missing data. I am interested in finding the columns for which there are fewer than 100 individuals with responses of 0. I can use an apply function to generate a table for each column, but I'm not certain whether I can subset a list based on some criterion as subset() is

Dear list, How can I add the mean and standard deviation to each of the boxplots using the example provided in the boxplot function? boxplot(len ~ dose, data = ToothGrowth, boxwex = 0.25, at = 1:3 - 0.2, subset = supp == "VC", col = "yellow", main = "Guinea Pigs' Tooth Growth", xlab = "Vitamin C dose mg",

How does one remove a column from a data frame when the name of the column to remove is stored in a variable? For Example: colname <- "LOT" newdf <- subset(olddf,select = - colname) The above statement will give an error, but thats what I'm trying to accomplish. If I had used: newdf <- subset(olddf,select = - LOT) then it would have worked, but as I said the column

I have a data frame containing columns which are factors. I use this to make boxplots for the data, with one box per factor. I would now like to get at the data in the data frame which corresponds to the outliers. I have so far found the $out, which gives "the values of any data points which lie beyond the extremes of the whiskers", but I haven't found anything which will let me get