search for: mu4

...0,2) sample2<-rnorm(100,50,3) sample3<-rnorm(100,20,2) sample4<-rnorm(100,40,1) mu1<-mean(sample1) ci.upper1<-mu1+2*2 ci.lower1<-mu1-2*2 mu2<-mean(sample2) ci.upper2<-mu2+2*3 ci.lower2<-mu2-2*3 mu3<-mean(sample3) ci.upper3<-mu3+2*2 ci.lower3<-mu3-2*2 mu4<-mean(sample4) ci.upper4<-mu4+2*1 ci.lower4<-mu4-2*1 categories<-c("A","B") mu<-cbind(mu1,mu2,mu3,mu4) ci.upper<-cbind(ci.upper1,ci.upper2,ci.upper3,ci.upper4) ci.lower<-cbind(ci.lower1,ci.lower2,ci.lower3,ci.lower4) segplot(mu~ci.upper+ci.lower|ca...

...lt;- pennw$inuidur1 > fw <- factor(wage) > Ik <- model.matrix(~fw-1) > I1 <- Ik[,1] > I2 <- Ik[,2] > I3 <- Ik[,3] > I4 <- Ik[,4] > I5 <- Ik[,5] > yelmon <- function(theta,x){ + mu1 <- theta[1] + mu2 <- theta[2] + mu3 <- theta[3] + mu4 <- theta[4] + mu5 <- theta[5] + beta <- theta[6] + logL <- sum((Ik*log((exp(mu2-(x*beta))/(1+exp(mu2-(x*beta))))-(exp(mu1-(x*beta))/(1+exp(mu1-(x*beta))))))+(Ik*log((exp(mu3-(x*beta))/(1+exp(mu3-(x*beta))))-(exp(mu2-(x*beta))/(1+exp(mu2-(x*beta))))))+(Ik*log((exp(mu4-(x*beta))/(1+exp...

...ary(methods)", true); re.eval("mu1 <- c(59.73, 27.94,89.67, 62.44)", true); re.eval("mu2<- c(57.81, 72.67, 82.97, 62.44)", true); re.eval("mu3<- c(45.66, 49.19, 53, 64.39)", true); re.eval("mu4<- c(70.39, 80.41, 89.67, 80)", true); re.eval("delta.C <- 1", true); re.eval("Acp <- rbind (c(mu4,mu2,delta.C), c(mu2,mu3,delta.C), c(mu3,mu1,delta.C))", true); re.eval("wt <- c(0.3,0.3,0.25,0.15)/1", true);...

Please help me in writing the R code for this problem. I've been solving this for 4 days. It was hard for me to solve it. It's a simulation problem in R. The problem is My true model is a normal mixture which is given as 0.5 N(-0.8,1) + 0.5 N(0.8,1). This model has two components. I will get a random sample of size 100 from this model. I will do this 300 times. That means, I will have

...randomly. For these 100 subsamples, I use the following 3 methods to calculate the standard error of standard deviation: 1. From book "Handbook of applicable mathematics", Walter Ledermann (chief editor) Volumn VI: Statistics, Part A, Lloyd, John Wiley & Sons. Page 30-32: var(S) = (mu4 - mu2^2)/(4 * mu2 * n) mu4 = E(X - mu)^4, mu2 = E(X - mu)^2, S^2 = sum(X - mu)^2/n The results are about: 0.00090 2. From http://davidmlane.com/hyperstat/A19196.html The results are about 0.00066 3. From http://mathworld.wolfram.com/StandardDeviationDistribution.html The results are about 0....

...comprehension) on 6 separate occasions. Initially (square zero) I want to treat the test time as a factor (with 6 levels). The students are of course ``random effects''. Later I want to look at reduced models, with the means at the 6 times following patterns: (mu1, mu2, mu2, mu3, mu3, mu4) or (mu1, mu1+theta, mu1+theta, mu1+2*theta, mu1+2*theta, mu1+3*theta) the idea begin that the tests are given ``in pairs'' at the beginning and end of the school year. Progress is expected over the school year, no progress over the two intervening summers. The summers fall between...

...Error t value ##(Intercept):1 -1.1527 0.33113 -3.4810 ##(Intercept):2 -1.2657 0.34139 -3.7073 ##(Intercept):3 -0.6633 0.29854 -2.2218 ##(Intercept):4 -1.3863 0.35355 -3.9210 ## ##Number of linear predictors: 4 ##Names of linear predictors: logit(mu1), ## logit(mu2), logit(mu3), logit(mu4) but that seems to be going to greater lengths than one should need to! Any comments and suggestions will be welcome! Best wishes to all, Ted. -------------------------------------------------------------------- E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk> Fax-to-email: +44 (0)...

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking