Re: [R] Computing multivariate normal probabilities. Was: Re: Problem with Numerical derivatives (numDeriv) and mvtnorm

2009-11-23 Thread SL
Hi Torsten,

Thanks for you comment.

If you have some free time to spare, partial derivatives with respect
to bounds and correlation coefficients would be great for pmvnorm! In
complex problems, optim is not very good at estimating the hessian
numerically and first order derivatives help to build an OPG
estimator, which is not very good as compared to an analytical hessian
but still much better than the numerical hessian provided by optim i
have found the problems I study.

Best,
Stephane

2009/11/23 Torsten Hothorn :
>
> On Sun, 22 Nov 2009, Ravi Varadhan wrote:
>
>>
>> Hi Torsten,
>>
>
> Hi Ravi,
>
>> It would be useful to "warn" the users that the multivariate normal
>> probability
>> calculated by "pmvnorm" using the GenzBretz algorithm is "random", i.e.
>> the result can vary between repeated executions of the function.
>
> only if a different seed is used.
>
>> This would prevent inappropriate use of pmvnorm such as computing
>> derivatives of it (see this email thread).
>>
>
> ?pmvt has "Randomized quasi-Monte Carlo methods are used for the
> computations." and appropriate references. In addition, the new book by Alan
> Genz and Frank Bretz covers all technical details in depth, so
> the procedures are well documented.
>
> Anyway, I'll add a statement to ?pmvnorm.
>
> Best wishes,
>
> Torsten
>
> __
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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Re: [R] Computing multivariate normal probabilities. Was: Re: Problem with Numerical derivatives (numDeriv) and mvtnorm

2009-11-23 Thread Torsten Hothorn


On Sun, 22 Nov 2009, Ravi Varadhan wrote:



Hi Torsten,



Hi Ravi,


It would be useful to "warn" the users that the multivariate normal probability
calculated by "pmvnorm" using the GenzBretz algorithm is "random", i.e. 
the result can vary between repeated executions of the function.


only if a different seed is used.

This 
would prevent inappropriate use of pmvnorm such as computing derivatives 
of it (see this email thread).




?pmvt has "Randomized quasi-Monte Carlo methods are used for the
computations." and appropriate references. In addition, the new book by 
Alan Genz and Frank Bretz covers all technical details in depth, so

the procedures are well documented.

Anyway, I'll add a statement to ?pmvnorm.

Best wishes,

Torsten

__
R-help@r-project.org 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.


Re: [R] Computing multivariate normal probabilities. Was: Re: Problem with Numerical derivatives (numDeriv) and mvtnorm

2009-11-22 Thread stephane Luchini
I'm now making some trials with sadmvn which provides results similar
to pmvnorm for optimization but I know compute my OPG estimator of the
covariance matrix with sadmvn (by the way Ravi, when I was refering to
"exist in theory" I was refering to the theory not to the computation
- would an appropriate "random" computation of partial derivative
work?).

Interestingly, mprobit also provides derivatives, exactly what I need.
Unfortunatly it fails to install on mac os X! (I don't want to install
windows in my system and my linux server is off for the moment).

Stephane

2009/11/22 Ravi Varadhan :
>
> Hi Torsten,
>
> It would be useful to "warn" the users that the multivariate normal 
> probability calculated by "pmvnorm" using the GenzBretz algorithm is 
> "random", i.e. the result can vary between repeated executions of the 
> function.  This would prevent inappropriate use of pmvnorm such as computing 
> derivatives of it (see this email thread).
>
> It seems that the other algorithm "Miwa" is deterministic, but not sure how 
> reliable it is (I had some trouble with it).
>
> It would also be useful in the help page to provide a link to two other 
> functions for evaluating multivariate normal probabilities:
>
> mnormt::sadmvn
> mprobit::mvnapp
>
> In particular, the `mvnapp' function of Harry Joe in "mprobit" package seems 
> to be very interesting as it provides very accurate results using asymptotic 
> expansions.
>
> Best,
> Ravi.
> 
>
> Ravi Varadhan, Ph.D.
> Assistant Professor,
> Division of Geriatric Medicine and Gerontology
> School of Medicine
> Johns Hopkins University
>
> Ph. (410) 502-2619
> email: rvarad...@jhmi.edu
>
>
> - Original Message -
> From: Ravi Varadhan 
> Date: Saturday, November 21, 2009 8:15 pm
> Subject: Re: [R] Problem with Numerical derivatives (numDeriv) and mvtnorm
> To: SL 
> Cc: r-help@r-project.org
>
>
>> Go back to your calculus text and review the definition of derivative:
>>
>> f'(x) = lim h -> 0  [f(x+h) - f(x)] / h
>>
>> when f(x) and f(x + h) are random variables, the above limit does not
>> exist.  In fact, f'(x) is also a random variable.
>>
>> Now, if you want the derivative you have to use a multivariate
>> integration algorithm that yields a deterministic value.  The function
>> `sadmvn' in the package "mnormt" can do this:
>>
>> require(mnormt)
>>
>> PP2 <- function(p){
>>    thetac <- p
>>    thetae <- 0.323340333
>>    thetab <- -0.280970036
>>    thetao <-  0.770768082
>>    ssigma  <- diag(4)
>>    ssigma[1,2] <-  0.229502120
>>    ssigma[1,3] <-  0.677949335
>>    ssigma[1,4] <-  0.552907745
>>    ssigma[2,3] <-  0.784263100
>>    ssigma[2,4] <-  0.374065025
>>    ssigma[3,4] <-  0.799238700
>>    ssigma[2,1] <-  ssigma[1,2]
>>    ssigma[3,1] <-  ssigma[1,3]
>>    ssigma[4,1] <-  ssigma[1,4]
>>    ssigma[3,2] <-  ssigma[2,3]
>>    ssigma[4,2] <-  ssigma[2,4]
>>    ssigma[4,3] <-  ssigma[3,4]
>>   pp <- sadmvn(lower=rep(-Inf, 4),
>> upper=c(thetac,thetae,thetab,thetao), mean=rep(0,4), varcov=ssigma, 
>> maxpt=10)
>> return(pp)
>> }
>>
>> xx <- -0.6675762
>>
>> P2(xx)
>>
>> require(numDeriv)
>>
>> grad(x=xx, func=PP2)
>>
>>
>> I hope this helps,
>> Ravi.
>>
>> 
>>
>> Ravi Varadhan, Ph.D.
>> Assistant Professor,
>> Division of Geriatric Medicine and Gerontology
>> School of Medicine
>> Johns Hopkins University
>>
>> Ph. (410) 502-2619
>> email: rvarad...@jhmi.edu
>>
>>
>> - Original Message -
>> From: SL 
>> Date: Saturday, November 21, 2009 2:42 pm
>> Subject: Re: [R] Problem with Numerical derivatives (numDeriv) and mvtnorm
>> To: r-help@r-project.org
>>
>>
>> > Thanks for you comment.
>> >
>> > There is certainly some "Monte Carlo sampling" involved in mvtnorm but
>> > why derivatives could not be computed? In theory, the derivatives
>> > exist (eg. bivariate probit). Moreover, when used with optim, there
>> > are some numerical derivatives computed... does it mean that mvtnorm
>> > cannot be used in an optimisation problem? I think it hard to believe.
>> >
>> > One possibility would be to use the analytical derivatives and then
>> a
>> > do-it-yourself integration but i was looking for something a bit more
>> > comprehensive. The mvtnorm package uses a specific way to compute
>> > pmvnorm and I'm far to do a good enough job so that derivatives can
>> > compare with what mvtnorm can do.
>> >
>> > Stef
>> >
>> > __
>> > R-help@r-project.org mailing list
>> >
>> > PLEASE do read the posting guide
>> > and provide commented, minimal, self-contained, reproducible code.
>>
>> __
>> R-help@r-project.org mailing list
>>
>> PLEASE do read the posting guide
>> and provide commented, minimal, self-contained, reproducible code.
>
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