[R] Peak Over Threshold values

[Tonja Krueger]

   I’m  sorry, but that‘s not exactly what I was looking for. I obviously
   didn’t explain properly:

   Within  my dataframe (df) I would like to find POT values that are not
   linked. In my definition two maximum values are linked if walevel does not
   fall below a certain value (the lower threshold value).

   walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91, 5.91,
   5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12,
   6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65,
   5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13,
   5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29,
   5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72,
   5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61,
   5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50,
   5.50, 5.49, 5.43, 5.39, 5.33, 5.26)

   day <- c(1:100)

   df <- data.frame(day,walevel)

   For example in my dataframe  a threshold value = 5.45 and an lower threshold
   value = 5.3 should lead to two maximum values because between the 2^nd and
   3^rd peak walevel does not fall below the lower threshold value.

   With  “clusters (…)” from “evd package”, I could find out POT values but
   even though I set a lower threshold value for my example dataframe I would
   get three maximum values instead of two.

   library(evd)

   clusters(df$walevel,u =5.45, ulow= 5.3, r = 1, cmax=T)

   clusters(df$walevel,u =5.45, ulow= 5.3, r = 1, plot=T)

   Changing r to 30 (for example) connects the 2^nd and 3^rd maximum events and
   gives out the right ‘end’ for the first extreme event but not for the second
   event. (Also I’d rather not use a time interval to prove that the events are
   linked)

   clusters(df$walevel,u =5.45, ulow= 5.3, r = 30, cmax=T)

   clusters(df$walevel,u =5.45, ulow= 5.3, r = 30, plot=T)

   What went wrong???

   Tonja
   -----Ursprüngliche Nachricht-----
   How about?
   hi.rle<-rle(walevel>5.79)
   lo.rle<-rle(walevel<5.36)
   plot(walevel)
   abline(h=5.8,col=2,lty=3)
   abline(h=5.35,col=3,lty=3)
   hi.lo.rle<-sort(c(cumsum(hi.rle$lengths),cumsum(lo.rle$lengths)))
   abline(v=hi.lo.rle)
   You can use the $values from the rle to sort things out. Probably
   want to ignore the end point at length(walevel).
   --
   Clint Bowman INTERNET: clint at ecy.wa.gov
   Air Quality Modeler INTERNET: clint at math.utah.edu
   Department of Ecology VOICE: (360) 407-6815
   PO Box 47600 FAX: (360) 407-7534
   Olympia, WA 98504-7600
   On Wed, 26 May 2010, Vito Muggeo (UniPa) wrote:
   > dear Tonja,
   > By plotting your data
   >
   > plot(df)
   >
   > it seems to me that you are looking for a piecewise linear relationships.
   If
   >  this is the case, have a look to the package segmented. You have to
   specify
   > or not the number and the starting values for the breakpoints
   >
   > library(segmented)
   > olm<-lm(walevel~day)
   >
   > #specify number and starting values for the breakpoints..
   > oseg<-segmented(olm, seg.Z=~day, psi=c(20,50,80))
   > plot(oseg,add=TRUE,col=2)
   > oseg$psi
   >
   > #or you can avoid to specify starting values for psi
   > oseg<-segmented(olm, seg.Z=~day,
   > psi=NA,control=seg.control(stop.if.error=FALSE,K=30))
   >
   > plot(oseg,add=TRUE,col=2)
   > oseg$psi
   >
   >
   > best,
   > vito
   >
   >
   > Tonja Krueger ha scritto:
   >> Dear List
   >>
   >> I hope you can help me: I’ve got a dataframe (df) within which I am
   >> looking
   >> for Peak Over Threshold values as well as the length of the events. An
   >> event
   >> starts when walevel equals 5.8 and it should end when walevel equals
   >> the
   >> lower threshold value (5.35).
   >>
   >> I tried “clusters (…)” from “evd package”, and varied r (see example)
   >> but it
   >> did not work for all events (again see example).
   >>
   >> walevel <- c(5.75, 5.75, 5.75, 5.76, 5.80, 5.82, 5.85, 5.86, 5.91,
   >> 5.91,
   >> 5.88, 5.92, 5.99, 6.02, 6.00, 6.08, 6.11, 6.10, 6.10, 6.11, 6.14, 6.12,
   >> 6.15, 6.17, 6.15, 6.08, 6.01, 5.95, 5.89, 5.83, 5.77, 5.72, 5.70, 5.65,
   >> 5.59, 5.51, 5.43, 5.33, 5.30, 5.25, 5.22, 5.21, 5.19, 5.19, 5.19, 5.13,
   >> 5.15, 5.07, 5.04, 5.02, 4.99, 5.05, 5.07, 5.12, 5.17, 5.22, 5.32, 5.29,
   >> 5.33, 5.33, 5.36, 5.37, 5.42, 5.43, 5.48, 5.55, 5.57, 5.66, 5.68, 5.72,
   >> 5.77, 5.79, 5.81, 5.80, 5.80, 5.77, 5.72, 5.70, 5.66, 5.62, 5.62, 5.61,
   >> 5.59, 5.57, 5.51, 5.47, 5.41, 5.39, 5.40, 5.40, 5.42, 5.45, 5.47, 5.50,
   >> 5.50, 5.49, 5.43, 5.39, 5.33, 5.26)
   >>
   >> day <- c(1:100)
   >>
   >> df <- data.frame(day,walevel)
   >>
   >> library(evd)
   >> clusters(df$walevel, u = 5.80, r = 1, ulow = 5.35, cmax = T, plot = T)
   >> clusters(df$walevel, u = 5.80, r = 50, ulow = 5.35, cmax = T, plot = T)
   >>
   >> What have I done wrong?
   >>
   >> Tonja
   >> ______________________________________________
   >> R-help at r-project.org mailing list
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   >> PLEASE do read the posting guide
   >> [2]http://www.R-project.org/posting-guide.html
   >> and provide commented, minimal, self-contained, reproducible code.
   >>
   >
   >

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