search for: rpareto

Hi, guys, I need to simulate Pareto distribution. But I found 'rpareto' didn't exist in R. And it seems that Pareto distribution don't have mathematical relationships with other distributions. What can I do? Thanks a lot. Ni --------------------------------- [[alternative HTML version deleted]]

...pareto distribution. It says in the documentation that the probabilty density of the pareto distribution The Pareto distribution has density f(y) = s (1 + y/(m (s-1)))^(-s-1)/(m (s-1)) where m is the mean parameter of the distribution and s is the dispersion Through my experimentation of using rpareto function from the library using m as the scale parameter *xmin* value and s as the shape parameter* a* , I found that the deviates generated are not all larger than *xmin*. This leads me to believe that m and s are not the shape and scale parameter respectively. What is m and s? Could it be define...

...lt;- list(alpha = alpha, b = b) class(result) <- "pareto" result} dpareto<-function(x, alpha,b) ifelse(x<b,0,alpha*(b^alpha)/(x^(alpha+1))) ppareto<-function(x, alpha,b) ifelse(x<b,0,1-(b/x)^alpha) qpareto<-function(p, alpha,b) b*exp(-log(1-p)/alpha) rpareto<-function(n, alpha,b) qpareto(runif(n),alpha=alpha,b=b) #LN lnormtfit_function(x,b, plot.it = F, lty = 1){ if (mode(x) != "numeric") stop("need numeric data") x <- x[!is.na(x)] x <- sort(x) y <- log(x-b)...

I am very new user of R project. Sir I am a research scholar. I am doing work on fitting distributions. Actually sir I want to know that what package is use to find parameters of pareto distribution by maximum likelihood method. and i want to find these parameters from my calculated data. Sir I am waiting for your positive response. Thanks

...4.508184 23.422685 28.96963 30.044882 35.502004 107.360714     My friends, group R . I hope you help me to comment on these results? And how can compute the variance of  Fs.   model.freq=expression(data=rpois(30)) model.sev=expression(data=rpareto(30,30)) Fs=aggregateDist("simulation",nb.simul=1000,model.freq,model.sev)   Thanks   Mohd PhD Student   Malaysia [[alternative HTML version deleted]]

...t;- length(X) m <- min(X) a <- n/sum(log(X)-log(m)) return( c(m,a) ) } par.eto.par <- c(s=pareto.MLE(data$T)[2], beta=pareto.MLE(data$T)[1]) [NOTE: data$T: the data we use] (2) Current random draw from an unrestricted pareto distribution: library(VGAM) random <- rpareto(l, location=beta, shape=s) [Note: s and beta are calculated in (1)] (3) What we need instead of step (2) is a random draw from an RESTRICTED pareto distribution, using the pareto parameters calculated (1), where random ? data$T This means: - start with one value from data$T. - Then make a ra...

...d poisson library(VGAM) # for pareto ditribution # parameters for pareto to generate mius nmiu <- 500; miupareto <- 3 ; disppareto <- 7; gmshape <- 1; gminvscale <- 0.5; gmscale <- 1/gminvscale; #generate means for control from Pareto distribution miuveccontrol <-rpareto(nmiu,miupareto,disppareto); # generate disperssions with gamma distribution dispvectpoiss <- rgamma(nmiu, gmshape, gminvscale, gmscale) foldchange <- runif(nmiu,min=0.5,max=3); miuvectreat <- foldchange*miuveccontrol; countvectreat <- matrix(0,nrow=nmiu,ncol=1); countveccontro...

...in http://tuvalu.santafe.edu/~aaronc/powerlaws/plfit.r. I obtained and tested the following fitting estimates based on dat1: xmin <- 0.01715686 alpha <- 2.381581 I then simply wanted to print the observed and fitted dists in one plot, so I ran: library(ggplot2) library(VGAM) dat2 <- rpareto(length(dat1), location=xmin, shape=alpha) hi1 <- hist(dat1, plot=FALSE, breaks="FD") hi2 <- hist(dat2, plot=FALSE, breaks="FD") y1 <- hi1$counts/sum(hi1$counts) y2 <- hi2$counts/sum(hi2$counts) x1 <- hi1$mids x2 <- hi2$mids qplot() + geom_line(aes(x=x1,y=y1...