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Bootstrap and parametric inference: successes and challenges

Young, A (Imperial)
Monday 07 January 2008, 15:30-16:30

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.

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