similar to: Fitting data to Pareto distribution

I would like to fit a Pareto Distribution and I am using the following codes fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) But the fitted values turn out to be the same for each observation. I guess the problem is with "ycf1 ~ 1", I would be grateful if anyone can give me some advice on how to define the formula. Many thanks -- View this

I would like to fit a Pareto Distribution and I am using the following codes. I thought the fitted (fit1) should be the fitted value for the data, is it correct? As the result of the "fitted" turns out to be a single value for all. fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) The result is fitted(fit) [,1] [1,] 0.07752694

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 would like to fit a Pareto Distribution and I am using the following codes. First, I thought the fitted (fit1) should be the fitted value for the data, is it correct? As the result of the "fitted" turns out to be the same value. fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") coef(fit, matrix=TRUE) summary(fit) fitted(fit) Secondly, how can I plot the

Dear R user, I am a newcomer and need help concerning 'draw a random number for a restricted area of a prareto distribution'. (1) For estimation of pareto distribution: >http://stats.stackexchange.com/questions/27426/how-do-i-fit-a-set-of-data-to-a-pareto-distribution-in-r< We calculate the pareto distribution (parameter estimation) as follows: pareto.MLE <- function(X) { n

Some background: I have some data on structural dependencies in a base of code artifacts. The dependency structure is reflected in terms of relative node degrees, with each node representing some code unit (just as an example). This gives me real data of the following form (sorry for the longish posting): dat1 <- c(0.00245098039215686, 0, 0, 0, 0, 0, 0, 0, 0.0563725490196078, 0, 0, 0,

The symptom triggering this email is that an S4 summary method sometimes refuses to be invoked, even when a package is explicitly loaded, if the first load of the package is implicit. It may or may not be specific to 'summary' methods and/or the 'VGAM' package. I've sent to R-devel because (i) it looks like some kind of bug to me, but I'm not sure; (ii) it's not

Dear, When i multiply the y of a regression by 10, I would expect that the coefficient would be multiply by 10 and the z value to stay constant. Here some reproducible code to support the case. *Ex 1* library(mvtnorm) library(VGAM) set.seed(1) x=rmvnorm(1000,sigma=matrix(c(1,0.75,0.75,1),2,2))

Hello. I have yet to receive a response to my previous post, so I may have done a poor job asking the question. So, here is the general question: how can I run a run a multivariate (more than one non-independent, response variables) ordered probit regression model? I've had success doing this in the univariate case using the vglm() function in the VGAM package. For example:

Dear R-users, I am new to R and would like to use it for fitting the zipf distribution to some numeric data that I have. Here's the snippet that I use: library(VGAM) X <- read.table(file("~\\mydata.txt", encoding="latin1")) w <- as.vector(t((X[2]))) w <- w/sum(w) y <- (1:length(w)) fit = vglm (y ~ 1, zipf, tra=TRUE, weight=w) zipf(N=NULL,

Dear R developers: I am trying to fit a PPO model using vglm from the library VGAM, and get an error while executing the code. Here is the data, code, and error: Data: first row is the column names. a = age, and 1,2,3, 4 and 5 are condition grades. a 1 2 3 4 5 1 1 0 0 0 0 2 84 2 7 10 2 3 16 0 6 6 2 4 13 0 3 4 0 5 0 0 0 1 0 Library(VGAM)

Hi , I know this question has been asked twice in the past but to my knowldege, it still hasn't been solved. I am doing a zero inflated binomial model using the VGAM package, I need to obtain p values for my Tvalues in the vglm output. code is as follows > mod2=vglm(dmat~Season+Diel+Tidal.phase+Tidal.cycle,zibinomial, data=mp1) > summary(mod2) Call: vglm(formula = dmat ~ Season +

Anyone know how to get p-values for the t-values from the coefficients produced in vglm? Attached is the code and output ? see comment added to output to show where I need p-values + print(paste("********** Using VGAM function gamma2 **********")) + modl2<- vglm(MidPoint~Count,gamma2,data=modl.subset,trace=TRUE,crit="c") + print(coef(modl2,matrix=TRUE))

Dear R-help gurus (and T.Yee, the VGAM maintainer) - I've been banging my head against the keyboard for too long now, hopefully someone can pick up on the errors of my ways... I am trying to use optim to fit a zero-inflated negative binomial distribution. No matter what I try I can't get optim to recognize my initial parameters. I think the problem is that dnbinom allows either

Hello, I want to generate data set from Cox PH model with gamma frailty effects. theta(parameter for frailty distribution)=2 beta=1.5 n=300 cluster size=30 number of clusters=10 I think I should first generate u from Gamma(Theta,theta) and then using this theta I could not decide how I should generate the survival times? Is there any package for this? or any document you could suggest? Any

Hi Folks, I wonderif someone who is familiar with the details of vglm in the VGAM package can assist me. I'm new to using it, and there doesn;t seem much in the documentation that's relevant to the question below. Say I have a vector x of 0/1 responses and another vector y of 0/1 responses, these in fact being a bivariate set of 0/1 responses equivalent to cbind(x,y). E.g.

Hi, R-users Could someone help me to understand this following error. I'm using vglm function in VGAM package Best regards and thank you for your ehlp ######## mydata <- read.table("Data2_overruns.csv", sep =";", header = T, row.names=NULL) > attach(mydata) > > y <- mydata$cat.event > phase.vol <-mydata$phase.vol > pilote <- mydata$pilote

Hi All, could anybody help me to understand what is this error means ? mydata=read.table("C:/Documents and Settings/angieb/Desktop/CommercialGL/cl_ilf_claimdata.csv",header=TRUE,sep=",") > names(mydata) [1] "ILFTable" "liabLimit" "AnnAggLimit" "DedAmt" "Loss" "TIL" >

R-Experts: I am using the vglm function of the VGAM library to perform proportional odds ordinal logistic regression. The issue that I would like help with concerns the format in which the response variable must be provided for this function to work correctly. Consider the following example: ------ library(VGAM) library(MASS) attach(pneumo) pneumo # Inspect the format of the original dataset

Dear all, I am trying to simulate from truncated Pareto distribution. I know there is a package called PtProcess for Pareto distribution...but it is not for truncated one. Can anyone please help me with this? Thanks in advance. Cassie [[alternative HTML version deleted]]