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Hai i just wanted to know how we can find the package of a dataset, eg: how can i find the package in which the dataset *iris* is present Ram [[alternative HTML version deleted]]

Can any one help me where i can find small standalone R programs that do things like: scatterplot, mean/median, kernel density estimation etc. Ram [[alternative HTML version deleted]]

The "maps" package has a function called "match.map", which is for map coloring . Its example is followed: # filled map showing Republican vote in 1900 # (figure 6 in the reference) data(state, package = "datasets") data(votes.repub) state.to.map <- match.map("state", state.name) x <- votes.repub[state.to.map, "1900"] gray.colors <-

Hi, Anybody know what are the common Standard statistical methods used for the analysis of a dataset,and anybody know which of these methods give similar results Ram [[alternative HTML version deleted]]

> My question then is, how to compute a similar procedure using the 'world' > database. Specifically, how can I access the country names in the 'world' > database to accomplish the translation to the country names in my dataset? > Is there any way to unpack the 'world' database to do the matching in an > external program? And does anybody now of other (more

Hi, I would like to plot a map of US counties using different colors. map() seems to be the function to use, e.g. library(maps); map('usa'); map('county', 'colorado', add=T,fill = T, col=c(1:5)) plots Colorado counties using colours 1 to 5. However, I want each color to represent a certain value - a value to be picked from a data frame. This code should show a

Hi everybody, I want to use the cluster package (Cluster Analysis Extended Rousseeuw et al.). I downloaded it from the CRAN and installed it on my linux system (fedora core 4). All seemed to be allright. But when trying to launch examples, I obtained the following message : > library(cluster) > data(votes.repub) > agn1 <- agnes(votes.repub, metric = "manhattan",

Dear list, is there a way how to add information to internal nodes (branching points) in dendrogram created via plot.agnes function (package cluster)? I wish to place colored circles on the nodes, but I don't know how to proceed... I'll be grateful for any suggestion Ond?ej -- Ond?ej Mikula Institute of Animal Physiology and Genetics Academy of Sciences of the Czech Republic Veveri 97,

Installing packages from binaries on Windows seems broken, when using mirrors that are up to date with CRAN install.packages( 'httr', type = 'binary', repos = "https://cran.rstudio.com/" ) Changing repos to the Kansas CRAN mirror installs the package as expected, but that could be because the KS mirror has not yet synced. Someone pointed out that the PACKAGES.gz

Removing 'type=binary' worked for me. install.packages( 'httr', repos = "https://cran.rstudio.com/" ) But I get an error when I select binary as type --- install.packages( 'httr', type = 'binary', repos = "https://cran.rstudio.com/" ) Error in install.packages : type 'binary' is not supported on this platform.

Dear colleagues: I've been storing up this question for a long time and apologize for the length and verbosity of it. I am having trouble in consulting with graduate students on their research projects. They are using surveys to investigate the sources of voter behavior or attitudes. They have predictors that are factors, some ordered, but I am never confident in telling them what

I am trying find a way to help the local Kerry campaign and it occurs to me that VOIP and Asterisk could be a big help. I have never worked on a presidential campaign before but I think they must be very telephone call intensive. Using VOIP to connect local, regional and national campaign offices and to keep volunteers in touch with each other would save lots of money that could be spent on

R-helpers! na.omit() can be used to remove rows with NA's but how can I remove columns ? and remember, which columns have been removed ? I guess I can do t(na.omit(t(o))) as shown below, but this probably creates a lot of overhead and I do not know which columns have been removed. Yours, R > o [,1] [,2] [,3] [1,] 1 NA 7 [2,] 2 NA 8 [3,] 3 NA 9 >

Hi All, I am a beginner in programming in r and please do forgive me if my question seems to be silly and sometimes not understandable. 1. we have a list of elements in a list say: ls<-list("N","E","E","N","P","E","M","Q","E","M") 2. We have an another list of tables in a list say: n <-

Hi, It is most probably just my R-ignorance, but I have following problem with using predict(). I train the model using 164 cases and then I try to use it on the data set with 35 cases, but I am getting 164 predictions ? R-code below illustrates in more detail what I am doing. Truly yours, R train = read.csv("train.csv", header = TRUE, row.names = "mol",

Dear R experts, Suppose I have a data frame of three variables: > foo <- data.frame(row=1:5, col=1:3, val=rnorm(15)) > foo row col val 1 1 1 -1.00631642 2 2 2 0.77715344 3 3 3 0.17358793 4 4 1 -1.67226988 5 5 2 1.08218836 6 1 3 1.32961329 7 2 1 -0.51186267 8 3 2 -1.20990127 9 4 3 -0.57786899 10 5 1 0.67102887 11 1 2

Hi! In a current project, I am fitting loess models to subsets of data in order to use the loess predicitons for normalization (similar to what is done in many microarray analyses). While working on this I ran into a problem when I tried to predict from the loess models and the data contained NAs or NaNs. I tracked down the problem to the fact that predict.loess will not return a value at all

Dear All: I do see I have weeks of codes in my console when I check with my arrow up keys. I have been clearing them with Control L but it seems to clear it clear the screen temporally. I do see the previous codes again when I open R the next day, after quitting the session! Q: How do I clear this? Thanks; YA -- View this message in context:

Dear list, Can somebody tell me how to invoke user-defined functions from script files during run-time? Basically I have (almost) one function per script file. I am thinking of something like #include in C++ import in Java/Python use in Perl No, I don't need my functions every time R is started. Neither I am thinking about writing building my functions into packages. I just

Hi all, I have a large data.frame, 1530 observation with 6 columns. I want to merge a 7th column, a transformation of the response variable (hospital admissions), namely trans<-sqrt(copd$admissions+0.25) trans<-data.frame(trans) And now when I do copd2<-merge(copd,trans) (copd being my original data.frame), R either crashes or is taking an extremely long time to do the computation. I