similar to: messenger on the mobile phone

Dear R users, Could somebody please help me to find a way of comparing nonlinear, non-nested models in R, where the number of parameters is not necessarily different? Here is a sample (growth rates, y, as a function of internal substrate concentration, x): x <- c(0.52, 1.21, 1.45, 1.64, 1.89, 2.14, 2.47, 3.20, 4.47, 5.31, 6.48) y <- c(0.00, 0.35, 0.41, 0.49, 0.58, 0.61, 0.71, 0.83, 0.98,

Hello, I'm trying to develop a box plot of time series data to look at the range in the data values over the entire period of record. My data initially starts out as a list of hourly data, and then I've been using this code to make this data into the final ts array. # Read in the station list stn.list <- read.csv("/home/kbennett/fews/stnlist3", as.is=T, header=F) # Read in

Hi, I got the same problem like http://tolstoy.newcastle.edu.au/R/devel/04/11/1204.html R crashes when I use the em function from the mclust package on univariate data and on a special case on bivariate data (when the matrix is not provided as written in the manual). It seems as if the problem is the format of the data to be analyzed. Operating System: Windows XP (SP2) R version: R-2.0.1 The

Dear list, I would like to plot points with two types of labels, one at the data point (the name of the point) and another offset a bit with another factor which is either of the two greek characters alpha or beta. I have tried to get the routine to plot a greek character with expression() or with substitute() and have not yet had any success. The following only plots the word in english in

Hello, As I am relatively new to the R environment this question may be either a) Really simple to answer b) Or I am overlooking something relatively simple. I am trying to add a VarIdent structure to my gam model which is fitting smoothing functions to the time variables year and month for a particular species. When I try to add the varIdent weights to variable Month I get this error returned.

Hi, I am using R to fit statistical models to data were the observations are means of the original data. R is used to calculate the mean before fitting the model. My problem is: When R calculates the means using tapply, the class of the means differs from the class of the original data, which gives me trouble when I want to use the original data to calculate model predictions. Here is a simple

Hi, I'm trying to obtain confidence intervals for auto and cross correlation estimates. I've adapted code made available by Stock and Watson that uses the Bartlett Kernel and the delta method. In R it runs really, really slow because of the loops it uses and I have 9 series that I'd like to examine (81 total combinations). It was easy enough to replace one of the while loops with a

Dear Gabor, Thanks for your reply. however: > tail(DJd) ^DJI.Close 2010-04-01 10927.07 2010-04-05 10973.55 2010-04-06 10969.99 2010-04-07 10897.52 2010-04-08 10927.07 *2010-04-09 10997.35* > tail(ag) 2009-11-30 10344.84 2009-12-31 10428.05 2010-01-31 10067.33 2010-02-28 10325.26 2010-03-31 10856.63 *2010-04-30 10997.35 * It seems the script "makes up"

Hi, We got a question about interpretating R-suqared. The actual outputs for a test dataset is X=(x1,x2, ..., xn). model 1 predicted the outputs as Y1=(y11,y12,..., y1n) model n predicted the outputs as Y2=(y21,y22,..., y2n) ... model m predicted the outputs as Ym=(ym1,ym2,..., ymn) Now we have two ways to calculate R squared to evaluate the average performance of committee model. (a)

Dear R-list I have been trying to make survreg fit a normal regression model with left truncated data, but unfortunately I am not able to figure out how to do it. The following survreg-call seems to work just fine when the observations are right censored: library(survival) n<-100000 #censored observations x<-rnorm(n) y<-rnorm(n,mean=x) d<-data.frame(x,y) d$ym<-pmin(y,0.5)

[[this bounced first, because it has 'help' in the Subject line ... -- Martin Maechler ]] I am a complete novice R programmer. (Though I know C quite well) I am trying to write some R code to do the following simulation. There is a 2-frame "movie" of noise and signal dots. the noise dots have random positions in each frame. The signal dots are placed randomly in frame 1,

hello, my name is Denny. I am new in this list. I am trying use multiple uplinks as describe in the lartc documentation (http://lartc.org/howto/lartc.rpdb.multiple-links.html) with squid transparent proxy in my gateway server. let me draw the configuration : /----------------- -----DSL1-----| \ |Transparent proxy |----Local network -----DSL2-----|

I would like to use lattice graphics to plot multiple functions (or groups or subpopulations) on the same plot region, using different line types "lty" or colors "col" to distinguish the functions (or groups). In traditional graphics, this seems straightforward: First plot all the data using 'type="n"', and subsequently execute a series of "points"

Hi, I wonder if anyone could advise me with this: I've been trying to make a standard curve in R with lm() of some standards from a spectrophotometer, so as I can express the curve as a formula, and so obtain values from my treated samples by plugging in readings into the formula, instead of trying to judge things by eye, with a curve drawn by hand. It is a curve and so I used the

R'ers: I was hoping I could get some direction on this. I have a dataset of the form: Y1,Y2,...,YM = f(X1,X2,...,XN), where N is >>> M The response data (Y1,Y2,...,YM) is frequency data, such that the sum of all Yi = 1.0. Both Xj and Yi are continuous variables. I'm trying to figure out the best approach(es) to solving for the model f() -- any ideas? I could solve

Greetings UseRs, Pls advise if there is a way to write a func that can be supplied to aggregate to compute weighted MeanAbsolute Dev (MAD). I am having trouble passing the correct weights from each group level and cannot see the code behind aggregate. But maybe 'aggregate' is not the best way to do that. > m1 <-

Hi everyone, newbee query! I've installed R 2.8.0 and tried to run this simple glm - x is no of cars in a given year, y is the number voted in an election that year while n is the population 18+: votes <- data.frame(x = c(0.62,0.77,0.71,0.74,0.77,0.86,1.13,1.44), + y=c(502,542,711,653,771,806,934,1123), n=

Hi Please help! I have one X101P and TDM400P in my asterisk Box When i make a call from * to PSTN, everything goes Ok, When the PSTN hangups or * hangups, the busy tone is detected and * disconnects the channel without problems. The problem occurs when the call comes from PSTN. When * hangups, the other end (at pstn) does not hangup, it only presents silence. Please tell me how to solve this

Hi all, I have H.323 Gateway, and i want to make a peer to route calls to this GW. But i don't know is oh323.conf supporting to add peer type entry with all feature. Please let me know how i can add H.323 GW type peer? -------- Yours, Abdul Lateef Computer Programmer HATIF COM Mob: +974 - 5405022 ICQ: 276994704 MSN: abdulzu@hotmail.com GoogleTalk: lateef.np@gmail.com YM!: abdul_zu Doha

I have "externnotify = /var/lib/asterisk/agi-bin/vm_notify.pl" so that when someone is left a voicemail it will call the person's mobile phone and prompt them with the new message. The perl script simply originates a call to a persons mobile phone and connects it to their voicemail using VoiceMailMain. Problem is when user hangs up from checking their messages, it runs the