# [R] multivariate integral with ADAPT when the parameter is close to boundary

Prof Brian Ripley ripley at stats.ox.ac.uk
Sun Oct 19 07:51:04 CEST 2008

```1) That integrand is a product, so you can do this a product of integrals,
and do those analytically.

2) Do you have any idea how extreme beta(0.005, 0.005) is?  See the
comment in the help for integrate:

Like all numerical integration routines, these evaluate the
function on a finite set of points.  If the function is
approximately constant (in particular, zero) over nearly all its
range it is possible that the result and error estimate may be
seriously wrong.

delta <- 1e-4
x <- seq(delta, 1-delta, delta)
plot(x, dbeta(x, 0.005, 0.005), type="l")
pbeta(0.9999, 0.005, 0.005) - pbeta(0.0001, 0.005, 0.005)

so 95% of the mass is outside the limits you set.

On Sun, 19 Oct 2008, Muhtar Osman wrote:

> Dear All,
>
> There is one problem I encountered when I used ADAPT to compute some
> 2-D integral w.r.t beta density.
>
> For example, when I try to run the following comments:
>
> fun2<-function(theta){return(dbeta(theta,0.005,0.005)*dbeta(theta,0.005,0.005))}
> int.fun2<-adapt(ndim=2,lo = c(0,0), up = c(1,1),functn = fun2,eps = 1e-4)
>
> It seems it will take very long time to run. Acturally, I stopped the
> program after it was running for like 20 minutes.
>
> I thought this might be due to the inclusion of the lower and upper in
> to the integral computation, so I tried to change the lower and upper
> limits:
>
> fun2<-function(theta){return(dbeta(theta,0.005,0.005)*dbeta(theta,0.005,0.005))}
> int.fun2<-adapt(ndim=2,lo = c(0.0001,0.0001), up =
> c(0.9999,0.9999),functn = fun2,eps = 1e-4)
>
> It only took few seconds to run, but it gave me the wrong result:
> int.fun2= 0.00202210665273673, whereas the correct result should be int.fun2=1.

No, that's the correct answer for the problem you set.

>
> I guess the reason for this is beta(0.005,0.005) has very high density
> close to the boundary (theta=0).
> So even letting  "lo = c(0.0001,0.0001)" will cause some loss of
> probability mass in the integral computation.
>
> I was wondering if anybody has encountered the similar problem before.
> Thanks.
>
> Muhtar Osman
> Dept.of Stats
> NCSU
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> and provide commented, minimal, self-contained, reproducible code.
>

--
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

```