Dear Ravi, Thank you for your answer.
The integrand I proposed was a dummy example for demonstration purposes. I experienced a similar slowdown in a real problem, where knowing in advance the shape of the integrand would not be so easy. Your advice is sound; I would have to study the underlying code of the two implementations to know where the difference lies. Delving into the source code and the algorithms gets quite technical though, so I was hoping someone already familiar with integrate's internals might shed some light. Thanks, baptiste On 12 November 2011 03:55, Ravi Varadhan <rvarad...@jhmi.edu> wrote: > The integrand is highly peaked. It is approximately an impulse function > where much of the mass is concentrated at a very small interval. Plot the > function and see for yourself. This is the likely cause of the problem. > > > > Other types of integrands where you could experience problems are: > integrands with singularity at either limit and slowly decaying oscillatory > integrands. As to why integrate performs better than adaptIntegrate in this > situation, I don’t know. You have to study the two implementations. > Wynn’s epsilon algorithm is an extrapolation method for improving the > convergence of a sequence. This could be an explanation for the better > performance, but I cannot say for sure. > > > > Hope this is helpful, > > 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 > > ______________________________________________ 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.
