search for: sim3

I want to load many files in the R. The names of the files are "Sim1.txt", " Sim2.txt", "Sim3.txt", "Sim4.txt", "Sim5.txt" and so on. Can I read them at one time? What should I do? I can give the same names in R. Thanks. For example: > tst=paste("Sim",1:20,".txt",sep="") # the file names > tst [1] "Sim1.txt" "Sim...

...t I am having trouble creating the objects b1,b2,b3,...,etc. b1 <- rigamma(50,1,1) theta1 <- rgamma(50,0.5,(1/b1)) sim1 <- rpois(50,theta1) b2 <- rigamma(50,1,1) theta2 <- rgamma(50,0.5,(1/b2)) sim2 <- rpois(50,theta2) b3 <- rigamma(50,1,1) theta3 <- rgamma(50,0.5,(1/b3)) sim3 <- rpois(50,theta3) b4 <- rigamma(50,1,1) theta4 <- rgamma(50,0.5,(1/b4)) sim4 <- rpois(50,theta4) b5 <- rigamma(50,1,1) theta5 <- rgamma(50,0.5,(1/b5)) sim5 <- rpois(50,theta5) par(mfrow=c(1,5)) boxplot(sim1) boxplot(sim2) boxplot(sim3) boxplot(sim4) boxplot(sim5); Thank...

I have just upgraded from R 1.7.3 to R 1.9.0 and have found that the predict function no longer works for rpart: > predict(hmmm,sim3[1:10,]) Error in predict.rpart(hmmm, sim3[1:10, ]) : couldn't find function "pred.rpart" I have re-installed the rpart package to no avail. Any ideas? Giles Hooker

2015-02-27 10:25 GMT-06:00 A J Stiles <asterisk_list at earthshod.co.uk>: > O.K. So what does your existing Dial() statement in extensions.conf look > like? > apology, put the gateway was sangoma but is a openvox , all my outgoing calls out for this context: [my-mobile-out] exten => _NXXXXXXX,n,Dial(SIP/1003/${EXTEN},55,rT) exten =>

...*Incoming* calls are not something that is within your control; they have already been routed onto a line by your telco. So you will need to speak to someone at your telco about doing this. As a temporary measure, you could try setting up divert-on-busy so SIM1 diverts to SIM2, SIM2 diverts to SIM3, SIM3 diverts to SIM4 and SIM4 diverts to SIM1. You can do this with specially-crafted Dial() statements, or by temporarily inserting the SIMs in an old mobile phone. See your telco's website for details of setting up call diversion. -- AJS Note: Originating address only accepts e-mai...

...), nmax = 20) set.seed(1) iso <- predict(g.dummy, newdata = xy, nsim = 10) gridded(iso) = ~x+y # spplot(iso,main="isotropic") # not essential for this question # I could make a dataframe like: diso<-data.frame(iso) diso[1:4,] # which results in: # x y sim1 sim2 sim3 sim4 sim5 sim6 sim7 sim8 sim9 sim10 # 1 1 1 0.4093776 1.0752794 -1.5654566 0.6183240 -2.196812 0.4545051 -0.06372423 -2.1544707 -1.131036 -0.4008869 # 2 2 1 0.8133436 0.9041941 -0.9712924 0.4319641 -2.432893 1.0770354 0.21302299 -1.6938882 -2.065350 -0.5331123 # 3 3 1...

...sim <- as.data.frame(sim) colnames(allsim) <- paste("sim",1:5,sep="") all <- cbind(rdtb,allsim) #-------------------------------- I don't understand why the simulation runs generate virtually identical values: > all[100:105,] rdtb sim1 sim2 sim3 sim4 sim5 100 2.3863636 1.065661 1.065661 1.065661 1.065661 1.065661 101 1.9318182 2.606093 2.606093 2.606093 2.606093 2.606093 102 2.2954545 3.854074 3.854074 3.854074 3.854074 3.854074 103 2.5882353 4.880240 4.880240 4.880240 4.880240 4.880240 104 2.0227273 4.917622 4.917622 4.917622...