similar to: Strange behaviour in plot and points?

I have installed R 1.6 for Linux from source, but unfortunately, I didn't check if the Xwindow headers were available, so I have installed it without Xwindows capabilities. Thus, I want to uninstall it and install it again properly with the required features, but I don't know how to uninstall R when built from source. I would appreciate any help on this. Thanks very much in advance!

Dear all, I would like to ask one question related to statistics, for specifically on defining dummy variables. As of now, I have come across 3 different kind of dummy variables (assuming I am working with Seasonal dummy, and number of season is 4): > dummy1 <- diag(4) > for(i in 1:3) dummy1 <- rbind(dummy1, diag(4)) > dummy1 <- dummy1[,-4] > > dummy2 <- dummy1 >

Dear R-users, I am trying to develop a function that takes another function as an argument, changes its default values and returns a list of things, among which the initial function with its default arguments changed. An example of what i will like to obtain below: ## initial function myfun <- function(x, a=19, b=21){ return(a * x + b) } ## this is the function i will like to create ##

I R-helpers #I have a data panel of thousands of firms, by year and industry and #one dummy variable that separates the firms in two categories: 1 if the firm have an auditor; 0 if not #and another variable the represents the firm dimension (total assets in thousand of euros) #I need to create two separated samples with the same number os firms where #one firm in the first have a corresponding

Dear R users, I would like to combine lattice plot (xyplot) and standard R plot (plot and plotCI) in an unique figure. I use the function "par()" to combine plot and plotCI and I use the function "print()" to combine xyplot. I tried to use these functions to combine xyplot and plotCI and plots but they do not work. Does anybody know how I can do this? Thank you very much in

Hello, Please let me know how I can troubleshoot this - driving me crazy! I have the following dovecot-ldap.conf file: hosts = ldap.ucmerced.edu dn=cn=natsciadmin,ou=Special Users,dc=ucmerced,dc=edu dnpass=******** ldap_version = 3 base = ou=People,dc=ucmerced,dc=edu deref = never scope = subtree user_attrs = uid user_filter = (&(ou=Natural

I almost go this liked but then I get the following: Mar 7 18:09:43 malaga dovecot: auth(default): ldap(jnorris,76.20.83.98): pass search: base=ou=People,dc=ucmerced,dc=edu scope=subtree filter=(&(uid=jnorris)) fields=uid,userPassword Mar 7 18:09:43 malaga dovecot: auth(default): ldap(jnorris,76.20.83.98): result: uid(user)=jnorris Mar 7 18:09:43 malaga dovecot: auth(default):

Hello all, the dovecot -> ldap connection is working correctly but I notice something in my maillog that is disturbing: dovecot.conf in the passdb section I have passdb passwd { } then it drops down into the ldap stuff. The user gets validated via this first and if it fails passes on to the ldap stuff. the problem is: in the file the user's unencrypted password is showing up as

Dear all, I have a simple question. I couldn't find a solution in the forums/R-user manual; I have also asked to my friends who use R, but couldn't get any answer from them either. I would appreciate any solutions. I want to write formatted text file like in Fortran. More specifically with the format choice of mine for any given line (more specifics are given below). The R function

Hi all: How can I calculate the cumulative variance (or variance for each component) in correspondence analysis? If were possible in ADE4 package Thank you -- Antonio Punzón Merino O__---- Instituto Español de Oceanografía c/ /'_ --- Centro Oceanográfico de Santander (*) \(*) -- Promontorio de San Martín S/N ~~~~~~~~~~ 39004-Santander; Spain PO BOX: 240 Tlf: +34 942 29 10 60 Fax: +34

Hello R users, I am working with the GAM to inspect the effect of some factors (year, area) and continuous variables (length, depth, latitude and longitude) on the intensity and prevalence of the common parasite Anisakis. I would like introduce interaction in my models, both "continuous variables-continuous variables" and "continuous variables-factor". I have read some

Hi I'm trying to measure the effect of a policy intervention (Box and Tiao, 1975). This query has to do with the coding of the model rather than with the particulars of my dataset, so I'm not providing the actual dataset (or a simulated one) in this case, apart from some general description. The time series are of length n=34 (annual observations between 1977 and 2010). The policy

Hello, Is there a better way to use paste such as: a = paste(colnames(list.indep)[1],colnames(list.indep)[2],colnames(list.indep)[3],colnames(list.indep)[4],colnames(list.indep)[5],sep="+") > a [1] "aa+dummy1+dummy2+bb+cc" I tried a = paste(colnames(list.indep)[1:5],sep="+") > a [1] "aa" "dummy1" "dummy2"

Dear list members, is it possible to set some options only inside a function so that the original options are restored once the function is finished or aborted due to an error? Until now I do something like: dummy=function() { old.options=options(error=dummy1()) .... options(old.options) } This works for most cases but when the function terminates because of an error and its last

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a linux system with 4 ethernet interfaces, eth0 goes to the internet, eth1, eth2, and eth3 are NAT''d LANs. I want to use an ingress filter to prioritize bandwidth (downstream from internet) to various IPs. I want to sett it up something like this.... eth0 <--[NAT]--> dummy0 <---> dummy1 <---> eth1,eth2,eth3 dummy1

Hi all, I've come across this issue today, and I think it might be a bug (or a feature ;) ). I've been testing Samba 3 on Debian Stable using the Samba packages from backports.org, which is says is version 3.0.2a. I've been testing Samba as a storage server in our NT4 Domain and have been playing with a bash script to set up user directories and permissions. Samba is set up with

Hi, I've tried to run the multiple imputation for longitudinal data using Pan in R. The trimmed data consist 10 individuals across 4 time points. Following the example in panex.R, I imputated the model with one y variable and only random intercept. It worked well. The next step for me is to imputate a model with one y variable and both random intercept and slope. The program ran well, but

Hello, I have a data frame > mdl.summary est.coef std.err t.stat intercept 0.0011625517 0.0002671437 4.351784 aa -0.0813727439 0.0163727943 -4.969997 dummy1 -0.0002534873 0.0001204000 -2.105376 dummy2 -0.0007784864 0.0001437537 -5.415417 bb -0.0002856727

Hello I'm having trouble figuring out how to use the output of "segmented()" with a new set of predictor values. Using the example of the help file: ??set.seed(12) xx<-1:100 zz<-runif(100) yy<-2+1.5*pmax(xx-35,0)-1.5*pmax(xx-70,0)+15*pmax(zz-.5,0)+rnorm(100,0,2) dati<-data.frame(x=xx,y=yy,z=zz) out.lm<-lm(y~x,data=dati) o<-## S3

hello ! i try to use a network technology on one single host, which wasn`t designed for that. to give a short overview of what i`m talking about: AoE is just like a "networked blockdevice" (just like nbd/enbd) - but without tcp/ip. AoE kernel driver is the "client end" (see this like an iSCSI initiator) - and an etherblade storage appliance is the "server end"