similar to: [] for R

What is 1. par.ests <- optimfit$par 2. fisher <- hessb(negloglik, par.ests, maxvalue=maxima); 3. varcov <- solve(fisher); 4. par.ses <- sqrt(diag(varcov)); Thanks a lot, fit.GEV <- function(maxima) { sigma0 <- sqrt((6. * var(maxima))/pi) mu0 <- mean(maxima) - 0.57722 * sigma0 xi0 <- 0.1 theta <- c(xi0, mu0, sigma0) #10/5/2007: removed assign() for maxima.nl

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) |

sigma0 <- sqrt((6. * var(maxima))/pi) What does the '.' do here? -- View this message in context: http://www.nabble.com/extra-.-tp25073255p25073255.html Sent from the R help mailing list archive at Nabble.com.

I created a EM algorithm for Generalized hyperbolic distribution. I want to estimate mutheldaplus, sigmatheldaplus, betasigmaplus in my code. After getting use these value , then my iteration have to be begin of this code. But I can not to do iteration part. Can you help me use my code and get iteration ? Do know any useful code for EM algorithm for Generalized Hyperbolic library(QRMlib)

In polr.R the (several) functions gmin and fmin contain the code > theta <- beta[pc + 1L:q] > gamm <- c(-100, cumsum(c(theta[1L], exp(theta[-1L]))), 100) That's bad. There's no reason to suppose beta[pc+1L] is larger than -100 or that the cumulative sum is smaller than 100. For practical datasets those assumptions are frequently violated, causing the

Hi R lovers! Are there any means to define and plot a function given the equation that specifies the function? For example I'd like to plot and work with the Gumbel Distribution density defined by Lambda(x)=exp(-exp(-x)) My question may appear very simple but I haven't got an idea yet about how to do that. I could plot something with x a vector/set of value but I don't know how to

Dear All, I am trying to do some simple mixture analyses. For instance, I have a sample of n observations and I suspect they come from two different exponential distributions with parameters rate1 and rate2, respectively. So, I want to estimate rate1, rate2, and the proportions of both kinds of individuals in the sample. I had a look at the packages mda and mclust, but they do not seem to do this

Dear useRs, upon request, the VGAM package (currently version 0.7-1) has been officially released on CRAN (the package has been at my website http://www.stat.auckland.ac.nz/~yee/VGAM for a number of years now). VGAM implements a general framework for several classes of regression models using iteratively reweighted least squares (IRLS). The key ideas are Fisher scoring, generalized linear and

I'm using R 2.8.1 on Ubuntu 8.10. I'm writing partly to ask what's wrong, partly to tell other users who search that there is a work around. The General Social Survey is a long standing series of surveys provided by NORC (National Opinion Research Center). I have downloaded some years of the survey data in SPSS format (here's the site:

Hey I'm not really sure what I should put on here, but I am having trouble with my R code. I am trying to get the p-values, R^2s etc for a number of different groups of variables that are all in one dataset. This is the code: #Stand counter st<-1 #Collections stands<-numeric(67) slopes<-numeric(67) intercepts<-numeric(67) mses<-numeric(67) rsquares<-numeric(67)

Hi, I am trying to fit a Johnson SB distribution using fitdist function in fitdistrplus Library. I have defined the Johnson SB distribution from ( http://www.ntrand.com/johnson-sb-distribution/) . But it gives me the follwing errors. Any help would be appreciated #xi = xi #lambda =l #delta =d #gamma = g djohn = function(x,xi,l,d,g) (d/(l*sqrt(2*pi)*((x-xi)/l)*(1-((x-xi)/l))))*exp[-0.5*(g +

Dear R-help readers, I am writing to you in order to ask you a few questions about distribution fitting in R. I am trying to find out whether the set of event interarrival times that I am currently analyzing is distributed with a Gamma or General Pareto distribution. The event arrival granularity is in minutes and interarrival times are in seconds, so the values I have are 0, 60, 120, 180, and

Hi, FWIW: /* Taken from R/src/main/unique.c */ static int requal(SEXP x, int i, SEXP y, int j) { if (i < 0 || j < 0) return 0; if (!ISNAN(REAL(x)[i]) && !ISNAN(REAL(y)[j])) return (REAL(x)[i] == REAL(y)[j]); else if (R_IsNA(REAL(x)[i]) && R_IsNA(REAL(y)[j])) return 1; else if (R_IsNaN(REAL(x)[i]) && R_IsNaN(REAL(y)[j])) return 1;

Dear helpers, I am using R version 2.5.1 to estimate a multinomial logit model using my own maximum likelihood function (I work with share data and the default function of R cannot deal with that). However, the computer (I have an Athlon XP 3200+ with 512 GB ram) takes quite a while to estimate the model. With 3 categories, 5 explanatory variables and roughly 5000 observations it takes 2-3 min.

Hello Eik: Thanks. I do not need to sample. Essentially, I have a do loop which produces 24 vectors of length of some length (say k=300) and 24 matrices of 300x300. Then, I simply need to? take the averages of these 24 vectors and matrices: x=(x1+x2+...+x24)/k y=(y1+y2+...+y24)/k I am just looking for ways to do this in a do loop, which requires initialization (to 0's) of x and y. My

Dear all, I am stuck on the following problem with integrate(). I have been out of luck using RSiteSearch().. My function is g2<-function(b,theta,xi,yi,sigma2){ xi<-cbind(1,xi) eta<-drop(xi%*%theta) num<-exp((eta + rep(b,length(eta)))*yi) den<- 1 + exp(eta + rep(b,length(eta))) result=(num/den)*exp((-b^2)/sigma2)/sqrt(2*pi*sigma2)

Hi, I'm trying to customize a window with 2 graphs. I'm able to do the first one with something like this general example par(mfrow=c(1,2),cex.axis=0.85,cex.lab=0.80,mai=c(1.3,1,0.5,0),las=3) bplot<-barplot(bar.values,names.arg=cf.names,width=0.5,ylab="% Area held") abline(h=0.3,lty=3,col="red") abline(h=0.1,lty=3,col="blue")

Dear All, I am starting to use the tikzDevice package, but I am experiencing some (minor problems). If I try to run the script at the end of the email, I get the following error Error in tools::texi2dvi("normal.tex", pdf = T) : Running 'texi2dvi' on 'normal.tex' failed. Messages: sh: /usr/bin/texi2dvi: not found How do I install the missing texi2dvi? I found some

Hi all, I am currently optimising a small portfolio I have created as a part of my research project in Excel. I am unable to find the appropriate package to port this into R. My problem set up is as follows Minimise ABS(Sum(Xi-Xi')+10*Sum(XiMi)/Mavg) Subject to: 0 <= Xi <= 0.05 ABS(Sum(Xi)) = 0.2 where Mi - Market Cap of Stock i Xi - Initial weight of Stock i Xi' - New weight of

Hi Steven, It's not entirely clear what you actually want to achieve in the end. As soon as you "know" x1, and assuming that the different "xi" do not differ in length in the real application, you know the length of the target vector. Instead of the loop, you can use 'Reduce' without having to initialize a starting vector. # generate sample vectors, put them in