[R] Beta stochastic simulation

[Duncan Murdoch]

On 9/15/2006 9:06 AM, Mark Pinkerton wrote:
> Yes, indeed I do. Is there any way I can dig into these a bit more? I
> have also just tried using the OO inverse beta from the distr package
> and this seems to work.

This is pretty irritating.  You were getting warnings from R that the 
calculations were inaccurate, and you didn't think that was worth 
mentioning?

I'll continue working on this after "Risk Management Solutions" 
compensates me for my wasted time, and pays me in advance for additional 
work.

Duncan Murdoch

> 
> 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:murdoch at stats.uwo.ca] 
> Sent: 15 September 2006 12:15
> To: Mark Pinkerton
> Cc: r-help at 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:murdoch at stats.uwo.ca]
>> Sent: 15 September 2006 00:45
>> To: Mark Pinkerton
>> Cc: r-help at 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
>> 
>> 
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