similar to: Lattice: multiple data sets on same plot

Hello, I can get the median for each factor, but I'd like another column to go with each factor. The nm column is a long name for the lvls column. So unique work except for the order can get messed up. Example: x =

Dear all, I am a relative novice with R, so please forgive any terrible errors... I am working with a GLM that describes a response variable as a function of a categorical variable with three levels and a continuous variable. These two predictor variables are believed to interact. An example of such a model follows at the bottom of this message, but here is a section of its summary table:

Hi, I am having some difficulties with matrix operations. It is a little hard to explain it so please bear with me. I have a very large data set, large enough that it needs to be split in parts in order to deal with. I can work things on these "parts" but the problem lies in adding together these parts for the final answer. So that been said, let's say that i split the data in 2

I need to apply a yearly inflation factor to some wages and supply some simple sums by work category. I have gone at it with a brute force "for" loop approach which seems okay as it is a small dataset. It looks a bit inelegant and given all the warnings in the Intro to R, etc, about using loops I wondered if anyone could suggest something a bit simpler or more efficent? Example:

Hi, I have the following dataset and I would like to create a dotplot with confidence limits: CAT1 CAT2 MEAN Lower Upper 1 1 1 0.619 0.392 0.845 2 1 10 1.774 1.030 2.518 3 1

Dear list, I have a vector (array, table row, whatever is best) of frequency values for categories (or bins), and I need to find the median category. Trivial to do by hand, but I was wondering if there is a means to do it in R in an elegant way. The obvious medioan(vector) returns the median frequency for the binns, and that is not what I want. i.e,: freq cat1 1 cat2 10

I have a categorical variable in a dataframe similar to the following... cat 1 1 3 2 4 I need to convert it to 4 dichotemous variables for each observations like... cat1 cat2 cat3 cat4 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 Thanks in advance! Shane

posting the question in r-help@ to get more feedback :-) thanks, Yun-Fang ----- Original Message ----- From: "Yun-Fang Juan" <yunfang at yahoo-inc.com> To: <s-news at wubios.wustl.edu> Sent: Tuesday, December 16, 2003 2:04 PM Subject: [S] plot stacked bar chart in R > Hi, > I am trying to plot a stacked bar chart in R but am not able to find the > documentation.

Hi all, I have some data as follows. Cat1 Cat2 Cat3 COG Counts A B C COG1 10 B D COG2 20 C COG3 30 D COG4 40 I would like to sum all the counts for each category: A B C D 10 30 40 60 >CAT2COG<-

Hi all, First time poster, so sorry if I commit some breech of posting etiquette. My problem is as follows. I have a data frame where each column represents a category and the individual data points in each category are binary responses (in this case they are actually 1's and 0's). What I want to extract are the counts for each category and put them in a vector. To do that I used the

Hi, I have a dataset with 6 categorical variables. I have used this following code to make the variables u1-u6 ordered factors and this works well. cat1cat2 cat3 cat4 cat5 cat6 ? 0 ? ?? 1 ? ? 1????? 0 ??? 0? ?? 1 ? 1 ? ?? 1 ? ? 0 ? ?? 0 ? ? 0 ? ? 0 ....... .... ############ data<-read,table("example.txt") data <- as.data.frame(lapply(data, ordered)) ############ Now,

Hello, I'm looking for a solution for the following problem: 1) I have a folder with several csv files; each contains a set of measurement values 2) The measurements of each file belong to a position in a two dimensional matrix (lets say "B02.csv" belongs to position 2,2 3) The size of the matrix is fix 4) I cannot assure to have a csv file for each position 5) Each position

Searched archives and found some old email threads on the topic. But mot exactly what I think I need. Suppose I have a datafile such as tmp. tmp <- data.frame(var1 = c(rnorm(1000), rnorm(1000, 1, 1)), var2 = gl(2, 1000)) I'd like a plot similar to the one below, but with an abline of v=0 in the lower panel and v=1 in the upper panel. Code below creates two lines in each panel, not quite

Hello all, I have been meaning to learn R for a while and have just subscribed to this list. I am planning to give R a shot at one of my live projects. I am looking to explore graphical features of R on my data below. Sample Data: Cat1 - Cat2 - Cat3 - Cat4 - NumPeople - Salary H - L - H - L - 100 - 50000 L - L - L - L - 40 - 30000 - H - H - - 100 - 45000 Cat1 through Cat4 are

Hello R help I have a dataframe, with 71 samples (rows) and 30 variables. I got linear models for some of the variables,? and I want to join fitted and residuals of these models to the data frame. Sometimes, these vectors have the same length of the dependant variable, but in a few cases, NA values can be found on my data, and therefore, both fitted and residuals have a few rows less than the

Initial comments about 5.00-pre11. 1_ Using ctrl+v at the boot prompt: SYSLINUX 5.00 5.00-pre11CHS Copyright ... Initial copyright notice when booting to Syslinux prompt: SYSLINUX 5.00 CHS 5.00-pre11 Copyright ... Request: make the ctrl+v result to be shown as the initial copyright notice (including order and space characters). 2_ Hello.c32 is still behaving differently than in 4.06.

I am trying to figure out how to write a conditional statement that will execute only if a specified variable is not empty. Right now my view looks like this: <dt>Building Regulations</dt> <% for link in @cat1 %> <dd><a href="<%= link.url %>"><%= link.title %></a></dd> <% end %> Action: @cat1 = Link.find(:all, :conditions

> From: Marc Schwartz > > On Fri, 2005-04-29 at 13:00 +0100, Gavin Simpson wrote: > > Dear List, > > > > Consider the following example: > > > > dat <- data.frame(var1 = rnorm(100), var2 = rnorm(100), > > var3 = rnorm(100), var4 = rnorm(100)) > > oldpar <- par(mfrow = c(2,2), no.readonly = TRUE) > >

Dear list, I'm currently trying to use the rms package to get predicted ordinal responses from a conditional ratio model. As you will see below, my model seems to fit well to the data, however, I'm having trouble getting predicted mean (or fitted) ordinal response values using the predict function. I have a feeling I'm missing something simple, however I haven't been able to

This is driving me nuts:-) I''ve brought it down to a simplified case where I''m rendering this rjs template: page.insert_html :top, ''cat1'', "<li>Some list item</li>" According to FireBug, this is what I''m actually getting in the browser: try { new Insertion.Top("cat1", "<li>Some list