Bootstrap and parametric inference: successes and challenges
Seminar Room 1, Newton Institute
We review parametric frequentist inference as it has developed over the last 25 years or so. Two main strands have emerged: analytic procedures based on small-sample asymptotics and simulation (bootstrap) approaches. We argue that the latter yield, with appropriate handling of nuisance parameters, a simple and flexible methodology, yet one which nevertheless retains the finer inferential components of parametric theory in an automatic fashion. Performance of the bootstrap methods, even in problems with high-dimensional parameters but small data sample sizes, points in favour of their being the method of choice in complex settings, such as those motivating this programme.
- http://stats.ma.ic.ac.uk/~ayoung/publications.html - Links to key papers.
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