similar to: ks.test not working?

Hi, I am performing GEV analysis on temperature/precipitation data and want to use the ks.boot function but I am unsure of how to implement it using the pgev distribution. For example: ks.test(data,pgev,shape,location,scale) ks.boot(data,(distribution parameters?),alternative="pgev",nboots=1000) Any advice? Apologies in advance if I have used the wrong email address. Regards, Louise

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Hi, I'm a second year Master's student in Applied Statistics. I am doing a project using average weekly U.S. regular gasoline prices (in cents, per gallon) from an Excel file (from the years 1990- May 2010). I want to find the probability that the average weekly U.S. regular gasoline prices (in the long term) goes over 400 cents a gallon (or $4.00 a gallon). I am using the

Hi, I'm new to R, and am trying to embed R into another application. I'm calling gev.fit() from the ismev package, and it is crashing somewhere inside it. gdb is not catching it, and valgrind is not showing any memory corruption issues. I suspect it's memory corruption, because it doesn't crash in exactly the same spot each time. I'm running R 2.12.2 on a 64 bit linux (Ubuntu

Hola a todos, Soy nuevo en R y estoy intentando modelizar una serie de datos no estacionarios usand la distribucion Generalizada de Valores Extremos GEV. ¿Podriais indicarme como se modeliza una tendencia polinómica (cuadrática, por ejemplo) en alguno de los 3 parámetros (situación, escala o forma)? He encontrado documentación a cerca de modelización linear o exponencial, pero no acabo de

Hi guys, I'm trying to use lmomco package. first I did the manual calculation on what is the estimates scale and location parameter given L-CV=0.2, L1=1000 L-moments and k (shape parameter) =- 0.1. so what i get is: location: 821.0445 scale: 260.7590 shape: -0.1000 #I assign this as GEV vectors using vec2par GEVpara2<-vec2par(c( 821.0445 , 260.7590 ,-0.1),'gev') #then I

Hi everyone, is there a function to fit a frechet distribution? The only thing I found is gev.fit from ismev which fits a generalized extreme value distribution (if shape>1 => Frechet) . Is there a function to only fit a frechet? Thank you Benjamin

hello everybody i want to use the maximum likelihood method to estimate FRECHET parameters of my sample data. Should it work with fitdistr in the package MASS? I only find how to do it for GEV, Gumbel, and almost all other distributions, but FRECHET? I would be very happy if somebody can tell me how to do fit the FRECHET distribution! Thanks Nadja Riedwyl

Hello, and please advise regarding any errors/omissions on my part. However, the documentation for R's tcplot function in the evd package appears to contain an error. I am using evd version 2.2-4 in R 2.14.0 with Windows XP. > data(portpirie) > mrlplot(portpirie) ## No Error > tlim <- c(3.6, 4.2) > tcplot(portpirie, tlim) ## Line from documentation Error in fpot(data, u[1],

hi, rgev function gives me random deviates and I have a data set which I am fitting to an EVD,IS there a way I can plot both observed and ideal evd on the same plot thankyou Rangesh

I am estimating a large model by groups. How do you save the results and?returns the associated quantiles? For this example I need a data frame n?? ?xi??????? mu????????beta 1?? 0.1033614? 2.5389580 0.9092611 2? ?0.3401922? 0.5192882 1.5290615 3?? 0.5130798? 0.5668308 1.2105666 I also want to apply gevrlevelPlot() for each "n" or group. ? #Example n <- c(1, 1, 1, 1, 1, 1, 2, 2, 2,

Hi All, I am performing GEV analysis on temperature/precipitation data using L moments: dim(data) [1] 145 192 156 Lmoments <- apply(data, 1:2, function(x) samlmu(x,nmom=4,sort.data=TRUE)) params_GEV <- apply(Lmoments,2:3,pelgev) location <- params_GEV[1,,] (xi) scale <- params_GEV[2,,] (alpha) shape <- params_GEV[3,,] (k) I want to use the ks.boot function but I am

Hello! I need to compare 2 datasets whether they come from the same distribution. I use function ks.boot{Matching}. And what is the confidence level of the p-value, returned by ks.boot function? The code is: set=read.table("http://stella.sai.msu.ru:8080/~gala/data/testsets.csv", header=T,sep=',') set1=set[!is.na(set$set1),'set1']

Dear R helpers, I need to use KS and AD test for Generalized Pareto and Generalized extreme value. E.g. if I need to use KS for Weibull, I have teh syntax ks.test(x.wei,"pweibull", shape=2,scale=1) Similarly, for AD I use ad.test(x, distr.fun, ...) My problem is fir given data, I have estimated the parameters of GPD and GEV using lmom. But I am not able to find out the distribution

Dear All- I am looking at the bivariate point process model for extreme values as described in Section 8.3.2 of Coles book. I am stuck at a very low level in being unable to reproduce the initial step of transforming the data to unit Frechet margins. In particular, I am unable to reproduce the wave-surge pairs distribution after transformation to Frechet scale (Figure 8.6 of Coles

Hi R helpers, Is there any function in R, which generates random numbers in case of (1) Generalized Extreme Value distribution and (2) Generalized PAreto distribution for the respective given set of parameters? Regards Maithili

Dear R helpers, How do you estimate the (Location, Scale, Shape) parameters of Generalized Extreme Value distribution using R? I have tried VGAM but just not able to write the R script. Please advise. With regards Maithili

I'm interested in doing multinomial logistic regression with equality constraints on some of the parameter values. For example, with categorical outcomes Y_1 (baseline), Y_2, and Y_3, and covariates X_1 and X_2, I might want to impose the equality constraint that \beta_{2,1} = \beta_{3,2} that is, that the effect of X_1 on the logit of Y_2 is the same as the effect of X_2 on the

Hi all, Is there a function to export a dataframe to a text file? I want to store a large set of data which I have saved in a dataframe in my workspace and copy and past doesn't cut it. Thank you, Benjamin

Hi I am fairly new to R and I would appreciate some help to hopefully a trivial problem. I created a function: summary.aggregate <- function(y, ...) { temp.mean <- aggregate(y, FUN=mean, ...) temp.sd <- aggregate(y, FUN=sd, ...) temp.length <- aggregate(y, FUN=length, ...) temp <- data.frame(cbind(mean=temp.mean$x,stdev=temp.sd$x,n=temp.length$x)) } this outputs e.g.: