search for: pgev

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 Wilson Louise Wilson Climate Projections Project Officer...

Hi, I am trying the following: library(ismev) library(evd) fit <- gev.fit(x,show=FALSE) ks.test(x,pgev,fit$mle[1],fit$mle[2],fit$mle[3]) but I am getting: Warning message: cannot compute correct p-values with ties in: ks.test(x, pgev, fit$mle[1], fit$mle[2], fit$mle[3]) where x is: [1] 239 38 1 43 22 1 5 9 15 6 1 9 156 25 3 100 6 [18] 5 100 10 103...

...pply(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 unsure of how to implement it using the pgev distribution. For example: ks.test(data[1,1],pgev,shape[1,1],location[1,1],scale[1,1]) ks.boot(data,(distribution parameters?),alternative=”pgev”,nboots=1000) Any advice? Regards, Louise Wilson -- *Louise Wilson* Climate Projections Project Officer CSIRO Climate Adaptation Flags...

...nd 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 extRemes program (in R), and I've already uploaded my data, and found the probability using the fitted GEV distribution (I used the pgev function from the evd package). I want to compare the results from the GEV distribution to those of the GPD distribution. I've already fitted the GPD distribution to my data (at a threshold of 400 cents, where there are 52 entries a year (for most years, at least)) and have obtained the...