search for: pareto1

...ad.table("C:/Documents and Settings/angieb/Desktop/CommercialGL/cl_ilf_claimdata.csv",header=TRUE,sep=",") > names(mydata) [1] "ILFTable" "liabLimit" "AnnAggLimit" "DedAmt" "Loss" "TIL" > fit=vglm(Loss~1,pareto1(location=alpha),trace=TRUE,crit="c") Error in eval(expr, envir, enclos) : object "Loss" not found [[alternative HTML version deleted]]

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 [2,] 0.07752694 [3,] 0.07752694 [4,] 0.07752694 [5,] 0.07752694 [6,] 0.07752694 [7,] 0.07752694 [8,] 0.07752694 [9,] 0.07752694 [10,] 0.07752694 [11,] 0.07752694 [12,...

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 message...

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 density for the fitted distribution? Many thanks. -- View this message in context: http://www.nabble.com/Pareto-Distribution-tf3908751.html#a11082669 Sent from the R help...

...I haven't managed to get any of them to make the right fits (as is evident when I check with the goodness of fit). One such option is: library(VGAM) b1 <- read.table(file("FitPareto_Values.txt", encoding="latin1")) b2 <- as.vector(t((b1[2]))) fit = vglm(b2 ~ 1, pareto1, trace=TRUE) With this code, R returns a coefficient for the intercept in the Pareto distribution as (-1.434) and this doesn't make any practical sense for the scenario that I am trying to model. Could anyone tell me where I could be going wrong? Or could you suggest alternative ways of...

...ltinomial Multinomial Logit Model nakagami Nakagami Distribution Family Function negbinomial Negative Binomial Distribution Family Function normal1 Univariate normal distribution paralogistic Paralogistic Distribution Family Function pareto1 Pareto and Truncated Pareto Distribution Family Functions paretoIV Pareto(IV/III/II) Distribution Family Functions persp.qrrvglm Perspective plot for QRR-VGLMs poissonff Poisson Family Function posbinomial Po...

...invexp Inverse Pareto invpareto Inverse paralogistic invparalogis Inverse Weibull invweibull Loggamma loggamma Loglogistic llogis Paralogistic paralogis Pareto pareto Single parameter Pareto pareto1 Transformed beta trbeta Transformed gamma trgamma All functions are coded in C for efficiency purposes and should behave exactly like the functions in base R. For all distributions that have a scale parameter, the corresponding functions have 'rate = 1' a...

...invexp Inverse Pareto invpareto Inverse paralogistic invparalogis Inverse Weibull invweibull Loggamma loggamma Loglogistic llogis Paralogistic paralogis Pareto pareto Single parameter Pareto pareto1 Transformed beta trbeta Transformed gamma trgamma All functions are coded in C for efficiency purposes and should behave exactly like the functions in base R. For all distributions that have a scale parameter, the corresponding functions have 'rate = 1' a...