similar to: Update VR_7.1-6

Is it possible to avoid the loop in the following function (or make the function otherwise more efficient) and can someone point me to a possible solution? (It would be great if hours could be reduced to seconds :-). # --------------------------------------------- RanEigen=function(items=x,cases=y,sample=z) { X=matrix(rnorm(cases*items),nrow=cases,byrow=F) S=crossprod(X-rep(1,cases) %*%

Can someone show me how to specify zero inflated poisson and zero inflated negative poisson models in R? I would like to replicate the example given in Long (1997: Regression Models for Categorical and Limited Dependent Variables) in Chapter 8.5 (pp. 242-247). TIA Dirk ************************************************* Dr. Dirk Enzmann Criminological Research Institute of Lower Saxony

I wonder whether the functions for skewness and kurtosis in the e1071 package are based on correct formulas. The functions in the package e1071 are: # -------------------------------------------- skewness <- function (x, na.rm = FALSE) { if (na.rm) x <- x[!is.na(x)] sum((x - mean(x))^3)/(length(x) * sd(x)^3) } # -------------------------------------------- and #

Just out of curiosity (and I hope that my question does not confuse those who intuitively understood the par(new=TRUE) statement right in the beginning): I would like to know whether beginners (learning R) had the same difficulty as I had: Intuitively I thought that par(new=TRUE) would draw a new plot (and not into an already existing plot) and that par(new=FALSE) would not draw a new plot

In trying to streamline various optimization functions, I would like to have a scratch pad of working data that is shared across a number of functions. These can be called from different levels within some wrapper functions for maximum likelihood and other such computations. I'm sure there are other applications that could benefit from this. Below are two approaches. One uses the <<-

Trying to select a subset of cases (rows of data) I encountered several problems: Firstly, because I did not read the help to read.spss() thoroughly enough, I treated the data read as a data frame. For example, dr2000 <- read.spss('myfile.sav') d <- subset(dr2000,RBINZ99 > 0) and thus received an error message (Object "RBINZ99" not found), because dr2000 is not a

I receive R-help messages in digest form that makes it difficult to answer a post. I noticed that my answer is not added to the thread (instead, a new thread is started) although I use the same subject line (starting with "Re: ") as the original post. Is there a solution (I prefer the digest to separate messages for several reasons and don't want to change my email reader)? The

Using ranef() (package nlme, version 3.1-75) with an 'lme' object I can obtain random effects for intercept and slope of a certain level (say: 1) - this corresponds to (say level 1) "residuals" in MLWin. Maybe I'm mistaken here, but the results are identical. However, if I try to get the standardized random effects adding the paramter "standard=T" to the

After loading the package "Matrix" (version 0.995-12), using the summary function with an lme (package nlme version 3.1-75) object results in an error message saying Fehler in dim(x) : kein Slot des Namens "Dim" f?r dieses Objekt der Klasse "correlation" (translated: 'Error in dim(x) : no slot of the name "Dim" for this object of class

Although I tried to find an answer in the manuals and archives, I cannot solve this (please excuse that my English and/or R programming skills are not good enough to state my problem more clearly): I want to write a function with an indeterminate (not pre-defined) number of arguments and think that I should use the "..." construct and the match.call() function. The goal is to write

Dear All, I have a codes which calculates the result of Ripley's K function of my data. I want to repeat this process 999 times. However, i am getting an error when i use the "for i in" function. Is there any way to repeat this analysis 999 times. Here are the codes i used ; data4 <- matrix(c(sample(id),data1),203,3) a <- data4[,1] random.case=data4[a==0,]

I'm sorry, but my previous message, as often happens, some brackets were wrong: Here are the correct formulas: sd = 1/n * sum((x-mean(x))^2) # (1) sd = 1/(n-1) * sum((x-mean(x))^2) # (2) This also occured in the last paragraph. Dirk ************************************************* Dr. Dirk Enzmann Institute of Criminal Sciences Dept. of Criminology Edmund-Siemers-Allee 1 D-20146

Hi, I have a dataset with x and y coordinates and in each point I have an identity of point, in some cases I can have more then one identity by point. My dataset is something like this: > x <- rep(c(1:4),4) > y <- rep(c(1:4),c(4,4,4,4)) > area1 <- sample(factor(rep(c("a","b","c","d"),4))) > area2 <-

Begin forwarded message: > Subject: R: Studdy Missing Data, differentiate between a percent > with in the valid answers and with in the different missing answers > take a look at the Website from Dirk Enzmann: > http://www2.jura.uni-hamburg.de/instkrim/kriminologie/Mitarbeiter/ > Enzmann/Software/Enzmann_Software.html > He provides a function called "freq.r" - maybe

I hesitate to post this question in the light of recent threads, indeed I have hesitated for several weeks, however I have come to a full stop and really need some help if I am going to progress. I am a new user of R for medical statistics. I have attempted to read all the relevant documents, but would welcome any suggestions as to what I have missed. I am trying to contruct "table 1"

Dear friends, I am studying the spatial distribution of trees in a tropical swamp forest in Brazil, and the spatial association between the trees and other forest and non forest elements. These are point pattern analysis of mapped data, preferentially done with the L function of Ripley. I have recently discovererd the R-project and would like to know whether it is possible to do these

I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",

i use the CrossTable (frome gregmic package) function to get such a table as below. but the percentage of the non-NA levels(here 1,2,3,4,5) is not totally 100%. is there any way to get a table that percentage of the non-NA levelsis totally 100%,as the SPSS' valid percentage.thank you! Cell Contents |-------------------------| | Count | | Row Percent |

Dear all, I cannot find a function which would allow drawing hist and density on the same graph. x <- seq(1,40,1) y <- 2*x+1+5*rnorm(length(x)) hist(y,freq = FALSE) plot(density(y)) thanks a lot for the help [[alternative HTML version deleted]]

Hi, with R v1.7.1 (=I don't recall I saw it before) I noticed that R CMD INSTALL sometimes generates nonsense information, e.g. "Bundle: NA", even if there was a correct DESCRIPTION file too. I turns out that it happens when a DESCRIPTION.in has empty lines at the end. I have observed this behavior on both Sun Solaris 9 and Windows XP Pro (but here I am using unsupported Cygwin w/