similar to: Displaying Results in Two Columns

I apologize if this posting shows up again, for some reason I wasn't able to post from a different account. So, here I am (reborn). Could I have some suggestions as to how I can display my results and their respective CIs in an aesthetically pleasing manner? Below is the example code. rm(list = ls()) set.seed(1) func <- function(d,t,beta,lambda,alpha,p.gamma,delta,B){ d <-

Full_Name: Alan Bain Version: 2.4.0 OS: XP Submission from: (NULL) (155.140.122.227) Code for pnchisq contains following if (tSml) { if (x> f+ theta+ 5*sqrt(2*(f+2*theta) ))){ return 1.; /* better than 0 --- but definately FIXME */ } } This needs to check which tail has been requested; it is only correct if the default lower_tail=1 has been requested; for upper tail should return 0

I got some R code that I don't understand. Question as comment in code //where is t comming from, what is phi inverse rAC <- function(name, n, d, theta){ #generic function for Archimedean copula simulation illegalpar <- switch(name, clayton = (theta < 0), gumbel = (theta < 1), frank = (theta < 0), BB9 = ((theta[1] < 1) | (theta[2] < 0)), GIG = ((theta[2] < 0) |

i=1 for(rate in c(2,4) ){ for(shape in c(1,3,5) ){ curve(dgamma(x,rate,shape),xlim=c(0,3),ylab="",col=i,lty=i,add=T) i=i+1 } } How can I add some legend to represent these lines? i.e. the legend is displayed as col=1 lty=1 lambda=2 theta=1 col=2 lty=2 lambda=2 theta=3 col=3 lty=3 lambda=2 theta=5 col=4 lty=4 lambda=4 theta=1 col=5 lty=5 lambda=4 theta=3 col=6 lty=6 lambda=4 theta=5

Dear all, Currently I am trying to integrate a function which depends on four variables, two of which are given, one is given in the integrate function, so there is one variable to integrate on. The code is as follows: Pmatrix = function(th) { P = matrix(nrow=6, ncol=6, data=0) P[1,1] = P[2,1]=P[3,2]=P[4,3]=P[5,4]=P[6,5]= exp(-th) P[,6] = 1-exp(-th) return(P)} lim.verd =

Dear experts! I have a minimization problem with non-linear constraint and Objective function(theta)=lambda*(Constr)^2-f(x,theta). Theta is a vector of parameters. I'd like to stop the optimization after the value of the constraint is less or equal some constant value, say d, and save the last computed value of the function. For this purpose, I thought to define the Objective function like

Dear R-users I need to calibrate kappa, rho, eta, theta, v0 in the following code, see below. However when I run it, I get: y <- function(kappahat, rhohat, etahat, thetahat, v0hat) {sum(difference(k, t, S0, X, r, implvol, q, kappahat, rhohat, etahat, thetahat, v0hat)^2)} > nlminb(start=list(kappa, rho, eta, theta, v0), objective = y, lower =lb, > upper =ub) Error in dots[[1L]][[1L]] :

Hi - I am doing a monte carlo experiment that requires to do a linear regression of a matrix of vectors of dependent variables on a fixed set of covariates (one regression per vector). I am wondering if anyone has any idea of how to speed up the computations in R. The code follows: #regression function #Linear regression code qreg <- function(y,x) { X=cbind(1,x) m<-lm.fit(y=y,x=X)

I have the following code, gibbs <-function(m,theta = 0.25, lambda =0.55, n =1){ alpha <- 1.5 beta <- 1.5 gamma <- 1.5 x<- array(0,c(m+1, 3)) x[1,1] <- theta x[1,2] <- lambda x[1,3]<- n for(t in 2:(m+1)){ x[t,1] <- rbinom(1, x[t-1,3], x[t-1,1]) x[t,2]<-rbeta(1, x[t-1,1] + alpha, x[t-1,3] - x[t-1,1] + beta) x[t,3]

Hello R community, following is my code and it shows error, can some one fix this error and explain why this occurs? gibbs <-function(m,n, theta = 0, lambda = 1){ alpha <- 1.5 beta <- 1.5 gamma <- 1.5 x<- array(0,c(m+1, 3)) x[1,1] <- theta x[1,2] <- lambda x[1,3]<- n for(t in 2:m+1){ x[t,1] <- rbinom(x[t-1,3], 1, x[t-1,1])

I am trying to write a lesson on maximum likelihood with Sweave. I get a surprising result with the following code, lec4.Snw: \documentclass[a4paper,12pt]{article} \usepackage[latin1]{inputenc} \title{Maximum likelihood} \author{G伱伓ran Brostr伱伓m} \begin{document} \maketitle <<fig=TRUE>>= ## Simulate Y: n <- 25 Y <- sum(rpois(n, lambda = 1)) Y ## Define minusloglik:

Hi guys. I have a dataset with 4 columns. In the first and second column I have the same qualitative variable referred to different teams of people. There are 10 teams in total and they compete against each other to perform a certain task whose result is stored in the third column for the team recorded in the first column, and in the fourth column for the team in the second column. For example,

Dear friends i am trying to fit an Ornstein-Uhlenbeck process by MAXIMUM LIKELYHOOD method. i found these formulas on http://www.sitmo.com/article/calibrating-the-ornstein-uhlenbeck-model/ this is the mean-reverting process http://r.789695.n4.nabble.com/file/n4637271/process.txt process.txt and this is the script that i am using....... ouFit.ML=function(spread) { n=length(spread)

Dears, I am writing sice having question about your R package "copula". I am using this package to fit my data with some of the 22 copulas mentioned in Nelsen 1999. However, when trying random number generator I have got some difficulties. For example when I have familie number A13 where cupola is equal to C(u,v) = exp(1-((1-log(u))^theta+(1-log(v))^theta-1)^(1/theta)) devuv =

hi everyone! i've got a problem in optimizing the following function fun <- function(theta){ theta <- rbind(beta,lambda) fun <- sum(exp(h(beta)%*%lambda)) fun } where h(beta) is h <- function(beta,...){ g1 <- matrix(0,b,M) g2 <- matrix(0,b,M) h1 <- matrix(0,b,1) h2 <- matrix(0,b,1) for(f in 1:M){ for(F in 1:b){ g1[F,f] <-

R Help List -- I have defined two time-series-vector-valued-functions, let them be f and g, and want to find the numeric derivative of f with respect to the variable x where f depends on x through g: (d/dx)(f (g(x) ) Moreover, x is a vector I tried this out the long way (naming every element of the x vector and then making the 'theta' argument in numericDeriv() the character vector of

Hello, I am struggling for some time now to estimate AR(1) process for commodity price time series. I did it in STATA but cannot get a result in R. The equation I want to estimate is: p(t)=a+b*p(t-1)+error Using STATA I get 0.92 for a, and 0.73 for b. Code that I use in R is: p<-matrix(data$p) # price at time t lp<-cbind(1,data$lp) # price at time t-1

Hello R and BUGS users, I am writing a heirarchical model in R to send to BUGS via R2WinBUGS and I am finding it difficult to get the model to run. I seem to be having two problems. 1) I can't seem to send variables classed as factors (Month), is there a way do this? 2) Checking the Log in WinBUGS I can see that the model is Syntactically correct, but Bugs is not able to recognise the the

Hello all, In the course of trying to implement the CDF of an InverseGammaDistribution, I have run across the need for an igamma() function. Several others have needed this function but the answers I have found so far are not totally clear to me. I'm writing for three reasons: 1) to present a small error in the docs 2) to clarify the approach we are expected to take 3) to request,for the

Dear Clara, Thanks for the reply. I am forwarding your message to the list, ok. When I wrote was a way of get further information to help the helpers. happy holidays, milton ---------- Forwarded message ---------- From: Clara Brück <clara_brueck@web.de> Date: 2009/12/30 Subject: Re: [R] Negbin Error Warnings To: milton ruser <milton.ruser@gmail.com> Dear Milton, Thanks for