R help - Aug 2010 - Displaying Results in Two Columns

Could I have some suggestions as to how (various ways) I can display my
confidence interval results?

rm(list = ls())
set.seed(1)
func <- function(d,t,beta,lambda,alpha,p.gamma,delta,B){
	d <- c(5,1,5,14,3,19,1,1,4,22)
	t <- c(94.32,15.72,62.88,125.76,5.24,31.44,1.048,1.048,2.096,10.48)
	post <- matrix(0, nrow = 11, ncol = B)
	theta <- c(lambda,beta)
	beta.hat <- 2.471546
	for(j in 1:B){
		for(i in 1:(B-1)){
			c.lambda <- rgamma(10,d+alpha,t+beta.hat)
			c.beta <- rgamma(1,10*alpha+p.gamma,delta+sum(lambda))
			c.theta <- c(c.lambda,c.beta)
			pi.func <-
prod((c.lambda/lambda)^(d+alpha-1)*exp(-t*(c.lambda-lambda)))*(c.beta/beta)^(10*alpha+p.gamma-1)*exp(-c.beta*(delta+sum(c.lambda))+beta*(delta+sum(lambda)))
			g.x <-
prod((beta.hat+t)^(alpha+d)*lambda^(alpha+d-1)*exp(-lambda*(beta.hat+t))/gamma(alpha+d))*(sum(lambda)+delta)^(p.gamma+10*alpha)*beta^(p.gamma+10*alpha-1)*exp(-beta*(sum(lambda)+delta))/gamma(p.gamma+10*alpha)
			g.y <-
prod((beta.hat+t)^(alpha+d)*c.lambda^(alpha+d-1)*exp(-lambda*(beta.hat+t))/gamma(alpha+d))*(sum(c.lambda)+delta)^(p.gamma+10*alpha)*c.beta^(p.gamma+10*alpha-1)*exp(-c.beta*(sum(c.lambda)+delta))/gamma(p.gamma+10*alpha)
			a <- pi.func*(g.x/g.y)
			if(a>1){
				theta<-c.theta
			}
			else
			theta <- theta+(c.theta-theta)*rbinom(1,1,alpha)
		}
		post[,j] <- theta
		#print(post[,j])
	}
	mean <- apply(post,1,mean)
	ci <- apply(post,1,quants)
	return(list("The Means" = mean, "The Corresponding Confidence
Intervals" = ci))
}
quants <- function(x){
	lo <- quantile(x,.025)
	hi <- quantile(x,.975)
	return(c(lo,hi))
}
(out <-
func(d,t,beta=1.5,lambda=rep(0.5,10),alpha=1.8,p.gamma=0.01,delta=1,B=100))

You could find several good examples on the first several results here:

http://www.google.com/search?sourceid=chrome&ie=UTF-8&q=plot.ci+R



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On Thu, Aug 19, 2010 at 2:47 AM, R Newbie <help0938450@gmail.com> wrote:
> Could I have some suggestions as to how (various ways) I can display my
> confidence interval results?
>
> rm(list = ls())
> set.seed(1)
> func <- function(d,t,beta,lambda,alpha,p.gamma,delta,B){
>        d <- c(5,1,5,14,3,19,1,1,4,22)
>        t <-
c(94.32,15.72,62.88,125.76,5.24,31.44,1.048,1.048,2.096,10.48)
>        post <- matrix(0, nrow = 11, ncol = B)
>        theta <- c(lambda,beta)
>        beta.hat <- 2.471546
>        for(j in 1:B){
>                for(i in 1:(B-1)){
>                        c.lambda <- rgamma(10,d+alpha,t+beta.hat)
>                        c.beta <-
> rgamma(1,10*alpha+p.gamma,delta+sum(lambda))
>                        c.theta <- c(c.lambda,c.beta)
>                        pi.func <-
>
prod((c.lambda/lambda)^(d+alpha-1)*exp(-t*(c.lambda-lambda)))*(c.beta/beta)^(10*alpha+p.gamma-1)*exp(-c.beta*(delta+sum(c.lambda))+beta*(delta+sum(lambda)))
>                        g.x <-
>
prod((beta.hat+t)^(alpha+d)*lambda^(alpha+d-1)*exp(-lambda*(beta.hat+t))/gamma(alpha+d))*(sum(lambda)+delta)^(p.gamma+10*alpha)*beta^(p.gamma+10*alpha-1)*exp(-beta*(sum(lambda)+delta))/gamma(p.gamma+10*alpha)
>                        g.y <-
>
prod((beta.hat+t)^(alpha+d)*c.lambda^(alpha+d-1)*exp(-lambda*(beta.hat+t))/gamma(alpha+d))*(sum(c.lambda)+delta)^(p.gamma+10*alpha)*c.beta^(p.gamma+10*alpha-1)*exp(-c.beta*(sum(c.lambda)+delta))/gamma(p.gamma+10*alpha)
>                        a <- pi.func*(g.x/g.y)
>                        if(a>1){
>                                theta<-c.theta
>                        }
>                        else
>                        theta <- theta+(c.theta-theta)*rbinom(1,1,alpha)
>                }
>                post[,j] <- theta
>                #print(post[,j])
>        }
>        mean <- apply(post,1,mean)
>        ci <- apply(post,1,quants)
>        return(list("The Means" = mean, "The Corresponding
Confidence
> Intervals" = ci))
> }
> quants <- function(x){
>        lo <- quantile(x,.025)
>        hi <- quantile(x,.975)
>        return(c(lo,hi))
> }
> (out <-
> func(d,t,beta=1.5,lambda=rep(0.5,10),alpha=1.8,p.gamma=0.01,delta=1,B=100))
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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