search for: sim2

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] "Sim...

...: is a matrix 202*263, that is 202 samples, and 263 independent variables num.compd<-nrow(x); # number of compounds diss.all<-0 for( i in 1:num.compd) for (j in 1:num.compd) if (i!=j) { S1<-sum(x[i,]*x[j,]) S2<-sum(x[i,]^2) S3<-sum(x[j,]^2) sim2<-S1/(S2+S3-S1) diss2<-1-sim2 diss.all<-diss.all+diss2} it will cost a long time to finish this computation! i really need "rapid" code to replace my code. thanks kevin -- View this message in context: http://r.789695.n4.nabble.com/how-to-replace-my-double-fo...

...en use the "lm" function without "weights". But the two methods yield different results. Would someone tell me which one is the correct way to do? Thanks in advance, and the code and output are as follows: > b1=474186/425906 > n=240 > sim1=rnorm(n,425906,40000) > sim2=matrix(0,n,1) > for (i in 1:(n)){ + sim2[i]=rnorm(1,sim1[i]*b1,sqrt(sim1[i])*50) + } > fit1=lm(sim2~-1+sim1,weights=sqrt(sim1)*50) > coef(fit1) sim1 1.116028 > y=sim2/(sqrt(sim1)*50) > x=sim1/(sqrt(sim1)*50) > fit2=lm(y~-1+x) > coef(fit2) x 1.116273 Sincerely, Yanw...

...help to write a more elegant version of my code? I am sure this can be put into a loop but 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(mf...

...e observations are normally distributed and the 2xk design is balanced, theory requires that the tests for interaction and row effects be independent. In my program, appended below, this would translate to cntT (approx)= cntR*cntI/N if all R routines were functioning correctly. They aren't. sim2=function(size,N,p){ cntR=0 cntC=0 cntI=0 cntT=0 cntP=0 for(i in 1:N){ #generate data v=gendata(size) #analyze after build(ing) design containing data lm.out=lm(yield~c*r,build(size,v)) av.out=anova(lm.out) #if column effect is significant, increment cntC...

To whoever this may concern I am trying to write a repeat loop and can't make out from the documentation on the website how exactly to construct the repeat, break structure of the loop. Below is the function sim2.dat that I am trying to create, in which firstly I create n random uniform(0,1) numbers. From there I assign values to k, P and F. From then on for each random number u[j] of u, I try to set up a repeat loop so that if u[j]>=F I alter P, k, and F and then compare u[j] to F again. I want to stop...

...need for reproducible research. The published docs and google have not yielded an answer, so any help greatly received. Thanks, Selwyn ## Example code snippet library(FracSim) ## simulate some 1d fractal data set.seed(1234) sim1 = fracsim.1d(h=0.5,k=1000,n=5000) ## reset the seed set.seed(1234) sim2 = fracsim.1d(h=0.5,k=1000,n=5000) table(sim1$process == sim2$process) ## not identical... [[alternative HTML version deleted]]

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 =>

I could use some advice. I've got 2 time series. Both cover approximately the same period of time (ie, 1940 to 2009). But one series has annual data and the other has monthly data. One refers to university enrollment; the other to unemployment rates. Both are currently in the same data frame. I'd like to use the monthly times series as a light grayscale background for a plot of the

Hello, I am a graduate student of University of Florida. I am trying to run a process variation model and I am facing the following error. ------------------------------------------------------------- Analysis of geostatistical data For an Introduction to geoR go to http://www.leg.ufpr.br/geoR geoR version 1.6-27 (built on 2009-10-15) is now loaded

...> channel 2 Ah. *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 addr...

Hello, I apologise if someone has already answered this but I searched and googled but didn't find anything. I have a matrix which gives me the similarity of each item to each other. I would like to turn this matrix into something like what they have in the graph package with the nodes and edges. http://cran.r-project.org/doc/packages/graph.pdf . However I cannot find a method to

...)) } allsim <- 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...

I could use some advice regarding xyplot. I've got 2 time series. Both cover approximately the same period of time (ie, 1940 to 2009). But one series has annual data and the other has monthly data. One refers to university enrollment; the other to unemployment rates. Both are currently in the same data frame. I'd like to use the monthly times series as a light grayscale background for a

...xp",15), 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 -0.5331...

Hi All I dont know if anyone else has noticed the same thing, but with 2 subsequent runs of the same syntax, I am getting exactly the same results. I was expecting that results differ slighlty, say in the 4th or 5th decimal place. Is this a specialty with R2WinBUGS? Does it have something to do with the seed value? Isnt the seed value reset everytime I restart winbugs? Thanks Toby

I am currently testing species co-occurrence patterns using null models and the oecosimu() function within the vegan() package. My issue is that none of the methods appear to be the ones that I want. The methods listed are r0, r1, r2, r2dtable, swap, tswap. However, I want to know how to go about implementing fixed row algorithms, as suggested in Gotelli 2000 in Ecology. Also, the null models