similar to: Converting a categorical variable to multiple dichotemous variables

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

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 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:

i am making a category tree and i iterate over the category using my counter_cache however it would show a different number than what was actually being represetned in the tree. Here is an example cat.children = [cat2, cat3] puts cat.children.size 2 puts cat.children_count 2 cat4.parent_id = cat.id cat4.save puts cat.children.size

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 all, I have two prodction servers with FreeBSD 5.4 (all security patches are applied). They running some services like dns, ssh, http, ftp, etc. But I woukd like to encrypt some services for some hosts with ipsec when it is accessed. For example: - DNS resolution: not encrypted. - DNS replication master-slave: encrypted by ipsec. - Telnet: encrypted by ipsec for some hosts. Deny

Hi, I am comparing the observed and fitted values of my GAM model, which includes the explanatory variables: longitude, depth, ssh, year and month. When I compare observed and fitted values for longitude, depth and ssh it works. But when I try to do it for month and year (which are as factors in the GAM model) it doesn't work. My observed and fitted values are exactly the same.. How is that

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

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 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

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

Hello, R friends... I am very new to R, and I need some help. I am trying to construct a simulation for my dissertation. I need to create 1000 datasets of 1000 subjects with the following variables... Treatment variable - Drawn from a binomial distribution (1 run, prob=.13) Covariate 1 - Drawn from a normal distribution (mean=100, sd=16) Covariate 2 - Drawn from a normal distribution

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 =

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

I'm new to R, but I'm trying to write a program for a dissertation that generates a dataset as follows... subject=1:1000 treat=rbinom(1*1000,1,.13) gender=rbinom(1*1000,1,.5) eth=runif(1*1000, min=1, max=4) cogat=rnorm(1*1000, 100, 16) map=rnorm(1*1000, 200, 9) simtest=data.frame (subject=subject, treat=treat, gender=gender, eth=round(eth,digits=0),

I have SLOW file transfers across samba to my Windows Server 2000 domain. I am using a built in 100bT Intel Pro NIC, I have tried the built in gigabit NIC and a PCI 3com, all with the same results. Using iperf, I get about 45-90Mb of bandwidth from my PC's to my samba server. I can pull it up by \\servername <file:///\\servername> or \\ipaddress <file:///\\ipaddress> with out

Hi, I have two data sets; one is a population and the other a sample of that population. I am trying to plot both on the same trellis display. # Example data set with two numerical attributes and two categorical pop <- data.frame(var1=rnorm(2000, 2000, 500), var2=rnorm(2000, 2000, 500)) cat<-(runif(2000)<=.5)+0 for(i in 1:length(cat)){ if(cat[i] == 0){ pop[i,"cat1"] =

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

I''m about to embark on a project and am seeking advice on my approach. I have an automotive site that needs to have shared categories. I''ve checked out different nested set, ancestral, acts_as_tree, acyclic plugins but feel they don''t exactly fit. So I am about to roll my own simple solution. Any feedback as to whether this looks good is appreciated. Essentially I