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Nonparametric inference under shape constraints: past, present and future

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  • UserRichard Samworth (Cambridge)
  • ClockThursday 22 January 2026, 16:00-17:00
  • HouseCMS MR2.

If you have a question about this talk, please contact HoD Secretary, DPMMS .

Traditionally, we think of statistical methods as being divided into parametric approaches, which can be restrictive, but where estimation is typically straightforward (e.g. using maximum likelihood) and nonparametric methods, which are more flexible but often require careful choices of tuning parameters. Nonparametric inference under shape constraints sits somewhere in the middle, seeking in some ways the best of both worlds. I will give an introduction to the area, providing some history, recent developments and a future outlook.

A wine reception in the central core will follow the talk.

This talk is part of the DPMMS Departmental Colloquia series.

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