[R] Function not working as I'd like

[David Carlson]

Your problem is here

ninetyoneclaims$total.chg>q

That produces a logical vector of TRUE/FALSE values, but the
length of the vector stays the same even though the number of
TRUEs is changing. Try 

sum(ninetyoneclaims$total.chg>q)

-------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org] On Behalf Of smugg55
Sent: Wednesday, October 23, 2013 9:25 AM
To: r-help at r-project.org
Subject: [R] Function not working as I'd like

Hey all,

So I wrote/borrowed some code (no, I'm not trying to claim all
of the work
I've done below as my own). Ideally what I'd like the code to do
is
calculate ep for each iteration of q. Here's the code:

> gpdriskmeasures = function(x , prob =
> c(0,.1,.2,.25,.3,.4,.5,.6,.7,.75,.8,.9,.95,.99))
+ {
+ xi = gpd.model$par.ests["xi"]
+ beta = gpd.model$par.ests["beta"]
+ u = gpd.model$threshold
+ q = u + (beta*((1-prob)^(-xi)-1))/xi
+ es = (q + (beta - xi * u))/(1 - xi)
+ ep =
1-length(ninetyoneclaims$total.chg[ninetyoneclaims$total.chg>q])
/length(ninetyoneclaims$total.chg)
+ ans = data.frame(p = prob, quantile = q, tail.expectation =
es,
empirical.prob = ep)
+ ans
+ }

Note that there are no problems pulling xi, beta, and u, and es
calculates
correctly. I'll also show what the results look like:

> gpdriskmeasures(ninetyoneclaims$total.chg)
      p  quantile tail.expectation empirical.prob
1  0.00  200000.0         336856.8      0.9878478
2  0.10  210058.6         351517.2      0.9878478
3  0.20  221704.1         368490.5      0.9878478
4  0.25  228270.1         378060.5      0.9878478

As you can see the empirical.prob (which is ep) is not
calculating
correctly, as that number should be decreasing as the quantile
(q)
increases.

Any help would be most appreciated! Thanks in advance for anyone
that can
help.



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