On 9/15/2006 7:51 AM, Mark Pinkerton wrote: > I have just installed 2.4.0 alpha and the problem persists. Here is the > output of the run:
When I run it, I get a series of warning messages from qbeta. Do you get those? Duncan Murdoch > >> # Summary stats >> summary(totals.losses1) > Min. 1st Qu. Median Mean 3rd Qu. Max. > 0 0 1284 1617000 685100 219200000 >> mean(totals.losses1) > [1] 1617219 >> sd(totals.losses1)/sqrt(length(totals.losses1)) > [1] 78863.17 >> >> summary(totals.losses2) > Min. 1st Qu. Median Mean 3rd Qu. Max. > 0 0 1422 2417000 819200 118200000 >> mean(totals.losses2) > [1] 2417471 >> sd(totals.losses2)/sqrt(length(totals.losses2)) > [1] 134866.0 > > Thanks, > Mark > > Mark Pinkerton > Risk Management Solutions > Peninsular House > 30 Monument Street > London EC3R 8HB > UK > > www.RMS.com > Tel: +44 20 7444 7783 > Fax: +44 20 7444 7601 > > -----Original Message----- > From: Duncan Murdoch [mailto:[EMAIL PROTECTED] > Sent: 15 September 2006 12:15 > To: Mark Pinkerton > Cc: r-help@stat.math.ethz.ch > Subject: Re: [R] Beta stochastic simulation > > On 9/15/2006 6:43 AM, Mark Pinkerton wrote: >> Hi Duncan, >> Thanks for having a look at this. Find attached a zip with all the >> relevant files to run the simulation. I am running this on Windows XP, > >> R version 2.3.1. > > Does the error still occur in a recent alpha build? It's downloadable > from CRAN, in cran.r-project.org/bin/windows/base/rtest.html (though I > notice the version there is a week old; I'd better kick the build > script). > > Duncan Murdoch > ' >> >> The correct result for the average annual loss, calculated using a >> battle tested FFT engine, is 1,609,361 The summary stats from my last >> run are below: >> >>> # Summary stats >>> summary(totals.losses1) >> Min. 1st Qu. Median Mean 3rd Qu. Max. >> 0 0 1142 1620000 698000 132500000 >>> mean(totals.losses1) >> [1] 1619891 >>> sd(totals.losses1)/sqrt(length(totals.losses1)) >> [1] 77949.25 >>> summary(totals.losses2) >> Min. 1st Qu. Median Mean 3rd Qu. Max. >> 0 0 2352 2341000 749700 141700000 >>> mean(totals.losses2) >> [1] 2341237 >>> sd(totals.losses2)/sqrt(length(totals.losses2)) >> [1] 129695.9 >> >> Thanks, >> Mark >> >> Mark Pinkerton >> Risk Management Solutions >> Peninsular House >> 30 Monument Street >> London EC3R 8HB >> UK >> >> www.RMS.com >> Tel: +44 20 7444 7783 >> Fax: +44 20 7444 7601 >> >> -----Original Message----- >> From: Duncan Murdoch [mailto:[EMAIL PROTECTED] >> Sent: 15 September 2006 00:45 >> To: Mark Pinkerton >> Cc: r-help@stat.math.ethz.ch >> Subject: Re: [R] Beta stochastic simulation >> >> On 9/14/2006 5:26 PM, Mark Pinkerton wrote: >>> Hi Duncan, >>> I had also validated the logic with a simple test which is why I was >> surprised by the differences I was seeing from tthe more complex >> simulation. I am running R on a Windows 2000 - I'll have to check >> which version at my desk tomorrow but it's pretty up to date, maybe 6 >> monthes old. Attached is a code snippet from my simulation program >> which is used to estimate multi-event annual losses for US hurricanes. > >> The event set being sampled from is quite large (~14000) with each >> event and account combination having a unique beta loss distribution. >> Simply swapping lines 23 and 24 has the effect on results that I >> mentioned in the previous email. The simulation is large enough that >> the MC error in the estimated means are negligible. >> >> The code you sent isn't usable, because it's missing your data. Could > >> you please do the following? >> >> - verify that the behaviour still happens in the current alpha test >> version >> >> - try to simplify the example code so someone else can run it? It >> could be that certain values of alpha and beta trigger a bug but the >> ones I tried were fine. >> >> Duncan Murdoch >> >> >> This message and any attachments contain information that may be RMS > Inc. >> confidential and/or privileged. If you are not the intended recipient > >> (or authorized to receive for the intended recipient), and have >> received this message in error, any use, disclosure or distribution is > strictly >> prohibited. If you have received this message in error, please > notify >> the sender immediately by replying to the e-mail and permanently >> deleting the message from your computer and/or storage system. > > > This message and any attachments contain information that may be RMS Inc. > confidential and/or privileged. If you are not the intended recipient > (or authorized to receive for the intended recipient), and have received > this message in error, any use, disclosure or distribution is strictly > prohibited. If you have received this message in error, please notify > the sender immediately by replying to the e-mail and permanently deleting > the message from your computer and/or storage system. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.