similar to: different legends in lattice panels

I'm looking for a tutorial or notes on the use of contrasts factor in linear model in R, I've found some mails and infos about in various documents about R, but I've probably missed a good review on this subject. -- Robert Espesser Laboratoire Parole et Langage UMR 6057, CNRS 29 Av. Robert Schuman 13621 AIX (FRANCE) Tel: +33 (0)4 42 95 36 26 Fax: +33 (0)4 42 59 50

Dear listers, The following command (derived from the example in the ?stars help page) works : data(mtcars) stars(mtcars[, 1:7]) But the following gives an error: stars(mtcars[1, 1:7]) Error in s.y[i, ] : incorrect number of dimensions I was expecting to have the star graph for the first line (Mazda Rx4) The following give an incorrect graph for the first two cars : stars(mtcars[1:2, 1:7])

Hi listers, A few days ago I posted a question about the use of the stars function on selected lines of a frame. Thanks to two helpers, a closer look at the scale argument allowed to partially solve the problem. Yet I still have a problem with stars. Allow me to explain what I intend to do (sorry for my poor English and the long post): I want to graph an activity index of a fish during the day

Sorry to keep asking elementary questions......I appreciate the help. I am trying to create a dotchart with the rows sorted according to the values, rather than the labels. When I try prof <- c('Accountant', 'Administrative assistant', 'Garment worker', 'Cook', 'Dentist', 'General practictioner', 'Graduate student', 'High level

Hi. I searched the list and didn't found nothing similar to this. I simplified my example like below: #I need calculate correlation (for example) between 2 columns classified by a third one at a data.frame, like below: #number of rows nr = 10 #the third column is to enforce that I need correlation on two variables only dataf =

Dear all, In order to ease the transition from SPSS to R for some of my colleagues, I am trying to create a function which would show the variables and their labels (if those exist), using function "label" in package Hmisc. A toy example would be this: my.data <- data.frame(age=c(24,35,28), gender=c("Male", "Female", "Male")) require(Hmisc)

Hi, I have a global data-frame in my R script. At some point in my script, I want to update certain columns of this data-frame by calling in an update function. The function looks like this: # get events data. This populates a global event data frame in the R-script events <- getEvents(con, eventsFilePath) # events has columns eventid, timeStamp, isSynchronized, timeDiff; with millions of

Hello; I am having a problems with the interpretation of models using ordered or unordered predictors. I am running models in lmer but I will try to give a simplified example data set using lm. Both in the example and in my real data set I use a predictor variable referring to 3 consecutive days of an experiment. It is a factor, and I thought it would be more correct to consider it ordered. Below

Hello, I have two problems in automating multiple glm(s) operations. The data file is tab delimited file with headers and two columns. like "ABC" "EFG" 1 2 2 3 3 4 dat <- read.table("FILENAME", header=TRUE, sep="\t", na.strings="NA", dec=".", strip.white=TRUE) dataf <- read.table("FILENAME", header=FALSE,

Hello All, I am trying to write a function which would operate on columns of a dataframe specified in parameters passed to that function. f = function(dataf, col1 = "column1", col2 = "column2") { dataf$col1 = dataf$col2 # just as an example } The above, of course, does not work as intended. In some languages one can force evaluation of a variable, and then

Hi, I like the formatting and the appearance of lattice plots. But I have not succeeded in gettting the right format in my plots with the lattice package in one of my applications. In?the code shown below, I start by constructing a general data frame and show my attempts with the lattice package commands. After that, I use the graphics package and show the kind of plot that I want to get. I would

Dear All I am reposting because I my problem is real issue and I have been working on this. I know this might be simple to those who know it ! Anyway I need help ! Let me clear my point. I have huge number of datapoints plotted using either base plot function or xyplot in lattice (I have preference to use lattice). name xvar p 1 M1 1 0.107983837 2 M2 11

Hi, I am writing a function that writes to a csv file for every call. However, for the subsequent calls, I want to append the data to the existing csv file without appending the column names again. I tried searching in the previous posts, but I am stuck with different errors. Here is what I am doing (dataF is a data-frame):- outputFilePath <- paste(getwd(), "/",

I'm trying to make a set of contour plots of bivariate kernel density estimates, showing three such plots overlaid, similar to this plot http://euclid.psych.yorku.ca/SCS/Private/Test/ridge-boot2.pdf except that I would like to have the contours *filled* (using transparent colors). To make this reproducible, I've saved the results of KernSmooth::bkde2D() in the following file:

In R, I'm imported a data frame of 2,321,123 by 4 called "dataF". I converted the data frame "dataF" to a matrix dataM <- as.matrix(dataF) Does R have an efficient routine to treat the special elements that contain "inf" in them. For example, can you separate the rows that have "inf" elements from the matrix into a separate matrix without

Hi, 1.) The "median" function does not work well. Please refer to the data below (same data is attached as txt-delimited). This is what I try to do in R: median ( dataf [2:9] ) I get warning: "needs numeric data" 2.) BUT if apply the median to a single vector: median ( dataf [,2]] ) then it works: 3.) How come the "median"

Dear R users, Here is my problem: # example data name <- c(paste ("M", 1:1000, sep = "")) xvar <- seq(1, 10000, 10) set.seed(134) p <- rnorm(1000, 0.15,0.05) dataf <- data.frame(name,xvar, p) plot (dataf$xvar,p) abline(h=0.05) # I can know which observation number is less than 0.05 which (dataf$p < 0.05) [1] 12 20 80 269 272 338 366 368 397 403 432 453

Hi list, It may be a FAQ, but I searched the web and Uni of Newcastle Maths and Stats and R mailing list archive on this issue but was unable to find a solution. I would appreciate any pointer to help me solving this. I am using R version 2.10.0 (2009-10-26) on linux mandriva 2010.0 I tried to install the XML_2.6-0.tar.gz package both with install.packages('XML', dep=T) from within R

Dear useRs, What is an efficient way to randomly sample from clustered data such that I get equal representation from each cluster? For example, let's say I want to randomly sample two cases from each cluster created by the "id" variable in the following data frame: > id<-c(rep("100", 4),rep("101", 3), rep("102", 6), rep("103",

Dear R-Experts I am sure this might look simple question for experts, at least is problem for me. I have a large data frame with over 1000 variables and each have different distribution( i.e. have different quantile). I want to create a new grouped data frame, where the new variables where the value falling in first (<25%), second (25% to <50%), third (50% to <75%) and fourth quantiles