similar to: selecting elements in vector

Hello I have this problem. I have a large matrix of this sort: > prova [,1] [,2] [,3] [,4] [1,] 3 3 3 3 [2,] 3 3 3 1 [3,] 1 3 3 3 [4,] 1 1 1 3 [5,] 3 1 1 3 [6,] 3 1 1 3 [7,] 1 3 1 3 [8,] 1 3 3 3 What I want to do is to count the number of sequences of ones and stack the results in a

Hello, I have the following problem. I am running simulations on possible states of a set of agents (1=employed, 0=unemployed). I store these simulated time series in a matrix like the following, where rows indicates time periods, columns the number of agents (4 agents and 8 periods in this case): Atr=[ 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 1 0 1 0 1 0

Hello everybody I have the following problem. I have to load a number of xls files from different folders (each xls file has the same number of columns, and different numbers of rows). Each xls file is named with a number, i.e. 12345.xls and is contained in a folder with same name, say 12345) Once loaded, I want to rbind all of them to obtain a single database. I think I successfully did the

dear all, This is a probably a silly question. If I type > grep("x",c("a.x" ,"b.x","a.xx"),value=TRUE) [1] "a.x" "b.x" "a.xx" Instead, I would like to obtain only "a.x" "b.x" How is it possible to get this result with grep()? many thanks for your attention, best, vito --

Dear all, It appears that MASS::polr() and Design::lrm() return the same point estimates but different st.errs when fitting proportional odds models, grade<-c(4,4,2,4,3,2,3,1,3,3,2,2,3,3,2,4,2,4,5,2,1,4,1,2,5,3,4,2,2,1) score<-c(525,533,545,582,581,576,572,609,559,543,576,525,574,582,574,471,595, 557,557,584,599,517,649,584,463,591,488,563,553,549) library(MASS) library(Design)

Dear all, I have tried to consider a correlation structure in lme (package lme4), but without success. I have used something like: > risul<-lme(y~x+ z , data=mydata, random=~ x | g, correlation = corAR1()) but the result is the same as: > risul<-lme(y~x+ z , data=mydata, random=~ x | g). Can anybody help me? Antonella ************************************************** Prof.

dear all, When I use all.vars(), I am interest in extracting only the variable names.. Here a simple example all.vars(as.formula(y~poly(x,k)+z)) returns [1] "y" "x" "k" "z" and I would like to obtain "y" "x" "z" Where is the trick? many thanks vito -- ==================================== Vito M.R. Muggeo Dip.to Sc

Dear list, I do not know if this is a bug. Let's suppose mat is a matrix derived from this code: > x<-rnorm(10) > y<-rnorm(10) > names(x)<-LETTERS[1:10] > names(y)<-LETTERS[1:10] > mat<-cbind(x,y) Now in R 2.0.1 I have: > names(dist(mat)) "A" "B" "C" "D" "E" "F" "G" "H"

Hi all, Just a random shot in the dark. Does anyone have/know of a function for the CDF of a generalized error dist? -- Elliot Williams (ewilliams at ucsd.edu) Economics Department, UC San Diego -------------- next part -------------- An embedded message was scrubbed... From: Elliot Williams <ewilliams at ucsd.edu> Subject: [R] Generalized Error Distribution (Exponential Power) CDF?

dear all, I would like to get the lme call without fitting the relevant model. library(nlme) data(Orthodont) fm1 <- lme(distance ~ age, random=list(Subject=~age),data = Orthodont) To get fm1$call without fitting the model I use call(): my.cc<-call("lme.formula", fixed= distance ~ age, random = list(Subject = ~age)) However the two calls are not the same (apart from the data

dear all, Is the following intentional? Am I missing anything in documentation? d<-data.frame(y=rnorm(10,5,.5),exp=rnorm(10), age=rnorm(10)) formula(lm(exp(y)~exp+age, data=d)) #--> exp(y) ~ exp + age formula(lm(exp(y)~., data=d)) #--> exp(y) ~ age variable 'exp' (maybe indicating "experience") is not included in the model. The same happens with 'log' (and

--- On Mon, 3/12/12, aleksandr shfets <a_shfets at mail.ru> wrote: > From: aleksandr shfets <a_shfets at mail.ru> > Subject: Fwd: Re[2]: [R] B-spline/smooth.basis derivative matrices > To: "Vassily Shvets" <shv736 at yahoo.com> > Received: Monday, March 12, 2012, 5:15 PM > > > > -------- ???????????? ????????? > -------- > ?? ????:

hi all, I'm facing a problem with a brand new installation on fedora 9. packages were updated right after the installation, so the samba packages are of the latest available version (3.2.0-17.fc9). at the first run were created all the tree of tdb files under /var/lib/samba. now I create a new user: [root@barbara Scrivania]# smbpasswd -a barbara New SMB password: Retype new SMB password:

Hi community, i have a samba server that work's great, but my friends of IT security said that is vulnerable without a firewall,  i try to set an iptables firewall using the official documentation but is not working (obviously), this ti my config: #!/bin/sh echo n Aplicando Reglas de Firewall... ## FLUSH de reglas iptables -F iptables -X iptables -Z iptables -t nat -F ## Establecemos

Hy (I hope this is the right list). 1. Mac porting I'm finishing the porting of R for Mac. I hope to finish it for the end of september. Thanks to the porting of R 0.64 by Ross (that he gave me) I succeded in this porting. This is the current state: Both R 1.1.1. and 1.2.0 works with minor modification to the original code. The Macintosh device has been updated to the new version of

Hello Samba experts, Please read all email because i'm desperate!!!!! I have problem on joining to LAN-s using Samba. Finally i got a solution to "see" booth workgroups on "Entire Network", but i'm having problem with stations located in LAN2. From any station located in LAN1, I can see LAN2 workgroup and the browse list with stations located in LAN2, but when

Hi, I downloaded both gee and geepack, and I am trying to understand the differences between the two libraries. I used the same data and estimated the same model, with a correlation structure autoregressive of order 1. Surprisingly for me, I found very different results. Coefficients are slightly different in value but sometimes opposite in sign. Moreover, the estimate of rho (correlation

Hi all, Could anybody recommend some easy-to-understand and example based notes/tutorials on how to use cubic splines to do filtering on multi-dimension data? I am confused by the 1-dimensional case, and more confused by multi-dimensional case. I found all the books suddenly become very abstract when it comes to this subject. They don't provide examples in R or Splus at all. Specifically,

Can anybody, please, explain me how many parameter are estimated using randomLCA? For examples, model "dentistry.lca2random" estimate 1 scale (or variance, b_j) parameter and 2 position parameters (a_cj)? Doesn't it? Do I need at least 4 diagnostic tests for such a model? What happens if I specify options blocksize and byclass? How many diagnostic tests (or rater) I need?

Dear List I hope you can help me: I?ve got a dataframe (df) within which I am looking for Peak Over Threshold values as well as the length of the events. An event starts when walevel equals 5.8 and it should end when walevel equals the lower threshold value (5.35). I tried ?clusters (?)? from ?evd package?, and varied r (see example) but it did not work for all events (again