similar to: Simple Question: adding points to a boxplot

Let's say I have a within-subject experiment with 2 observables, obs1 and ob2 and 2 independent factors, fac1 and fac2. I can do summary( aov( obs1~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) summary( aov( obs2~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) to test the 2 observables separately. > summary( fit<-manova( cbind(obs1,obs2)~fac1*fac2 + Error(Subject/(fac1*fac2)) ) ) gives

Dear WizaRds, After consulting different sources I am still unable to understand the correct use of return() in nested functions. To illustrate the problem: f <- function(x,y,type){ est1<-function(x,y){ z=x+y out(x,y,z)} est2<-function(x,y){ z=x*y out(x,y,z)} out<-function(x,y,z) return(x,y,z) if (type=="est1") est1(x,y) if (type=="est2") est2(x,y) }

Dear r-helpers, Could you please tell me what's missing: rbind(paste('txt.est',1:24, sep = '')) txt.est1, ... txt.est24 are vectors that I wish to rbind. _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road

Dear R-mates, # Here's what I am trying to do. I have a dataset like this: id = c(rep(1,8), rep(2,8)) dur1 <- c( 17,18,19,18,24,19,24,24 ) est1 <- c( rep(1,5), rep(2,3) ) dur2 <- c(1,1,3,4,8,12,13,14) est2 <- rep(1,8) mydata = data.frame(id, estat=c(est1, est2), durat=c(dur1, dur2)) # I want to one have this: id = c(rep(1,8), rep(2,8))

Hi, I have Forecast Class and Observed Class in a data matrix as below. > Sample1 FCT OBS 1 1 5 2 2 4 3 3- 3+ 4 3 3 5 3+ 3- 6 4 2 7 5 1 I want to find the difference between Observed and Forecast Classes. How can I get this done? I tried to following to convert the 1 through 5 classes, to 1 through 7 for both OBS and FCT column. > Sample1$OBS2 <- Sample1$OBS

Does anyone have an R Syntax Highlighting file {userDefineLang.xml} for NotePad++?? I've started one, but I'm not so happy with it. Robert Farley Metro 1 Gateway Plaza Mail Stop 99-23-7 Los Angeles, CA 90012-2952 Voice: (213)922-2532 Fax: (213)922-2868 www.Metro.net [[alternative HTML version deleted]]

Hi, newbie question. I have a data-frame with 3 named columns: Name, Obs1, Obs2. The Name column members are made of alphanumeric characters: T1, T2, T3 etc. I would like to acess only that subset of the data-frame with Name == T44. X <- dataframe[dataframe$Name=='T44'] does not work. Any ideas on how to do this? I'm sure I'm missing a simple concept here. Thanks, Anjan --

I'm trying to prepare some cross tabs, looking at a number of variables against a variable "connector" which has 2 values: "OD Passenger" and " Connector". When I produce a xtabs one way I have observations under "Connector" but against a different variable "Connector" shows all 0 values. What is wrong? I've looked into the na commands

I have recently begun experimenting with Asterisk, and have been mightily impressed by its capabilities and flexibility. I have run across one problem, however, that challenges my ability to use it as a production system. My Asterisk box has a public Internet IP, and works great with SIP (ATA 186) clients that also have public IP addresses. Unfortunately, most of the locations that I would

I can't figure out the syntax I need to get subset to work. I'm trying to split my dataframe into two parts. I'm sure this is a simple issue, but I'm stumped. I either get all or none of the original "rows". > XTTable <- xtabs( ~ direction_ , SurveyData) > XTTable direction_ EASTBOUND

I have a dataframe from an On-Board Survey with weights ("expwgt") and variables for up to 8 used lines: VEH1 through VEH8. The lines are labeled "MT-..1" through "MT-902". I want to know how many transfers there are between MT-802 and MT-901. That is, when one of them is VEHx and the other is VEHx+1 or VEHx-1 E.g. {VEH1 = MT-802 AND VEH2 = MT-901 } plus {VEH2 =

Hello, I want to do fisher test for the rows in data file which has value less than 5 otherwise chi square test .The p values from both test should be stored in one resulted file. but there is some problem with bold if statement. I don't know how implement this line properly. x = cbind(obs1,obs2,exp1,exp2) a = matrix(c(0,0,0,0), ncol=2, byrow =TRUE) #matrix with initialized values

I obviously don't know what I'm doing. I want to create "ByEBNum" as a data frame, but it comes out as a list. How do I make it a data frame? > EBNumStn <- c(673.65, 800, 1000, 1000, 800, 700, 600, 500, 400, 200, 50, 50 ) > ByEBNum <- data.frame(c(1:12),EBNumStn) > typeof(EBNumStn) [1] "double" > typeof(c(1:12)) [1]

I have been experiencing a rather odd issue with my (newly connected) T100P card. It is installed in my Asterisk server, which is working great with SIP clients. The card is connected to a channelized T-1 line (24 channels). The odd bit is that outgoing calls (Asterisk --> T-1 --> PSTN) works just fine. However, incoming calls (PSTN --> T-1 --> Asterisk) are dropped after about 20

First the R question. I have the results of a rather large survey (thousands of forms, each with dozens of questions) with some existing weights and expansion factors. I wish to add additional weighting factors, based on new information that elements of certain variables should appear in certain proportions. Where should I look in R to develop what is essentially an N-dimensional balancing

I'm plotting some trip length frequencies using the following code: plot( density(zTestData$Distance, weights=zTestData$Actual), xlim=c(0,10), main="Test TLFD", xlab="Distance", col=6 ) lines(density(zTestData$Distance, weights=zTestData$FlatWeight), col=2) lines(density(zTestData$Distance, weights=zTestData$BrdWeight ), col=3) which works fine except the

Hi I have developed the code below. I am worried that the parameters I want to be estimated are "not being found" when I ran my code. Is there a way I can code them so that R recognize that they should be estimated. This is the error I am getting. > out1=optim(llik,par=start.par) Error in pnorm(au_j, mean = b_j * R_m, sd = sigma_j) : object 'au_j' not found #Yet

Hi, I have a data set that I'd like to run logistic regressions on, using ddply to speed up the computation of many models with different combinations of variables. I would like to run regressions on every unique two-variable combination in a portion of my data set, but I can't quite figure out how to do using ddply. The data set looks like this, with "status" as

I want to calculate "expansion factors" for elements in my dataframe based on a 2-d cross classification. Since I'll have "missing values" (many combinations will have no record) I'll need a second "expansion factor" for each "row". I've included my "work to date" below, but I'm not very close to getting this right. My

Couple of little things I noticed with a new RELENG_7 AMD64 box (as of yesterday) ifstat from the ports cannot seem to find interfaces for some reason ? It works fine on i386 [ns8]# ifstat -b ifstat: no interfaces to monitor! [ns8]# [ns8]# ifconfig em0: flags=8843<UP,BROADCAST,RUNNING,SIMPLEX,MULTICAST> metric 0 mtu 1500