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統計数学セミナー
過去の記録 ～04/18｜次回の予定｜今後の予定 04/19～
| 担当者 | 吉田朋広、荻原哲平、小池祐太 |
|---|---|
| セミナーURL | http://www.sigmath.es.osaka-u.ac.jp/~kamatani/statseminar/ |
| 目的 | 確率統計学およびその関連領域に関する研究発表, 研究紹介を行う. |
2021年03月24日(水)
14:30-16:00 オンライン開催
参考URLのGoogle Formより３日前までに参加登録してください。 ご登録後、会議参加に必要なURLを送付いたします。
Rachel Fewster 氏 (University of Auckland)
Stochastic modelling in ecology: why is it interesting? (ENGLISH)
https://docs.google.com/forms/d/e/1FAIpQLSf05P9fCZ5Wkasc7clW1XBpkeONPSjPKuCkNYb3oIqnOAu5Mg/viewform
参考URLのGoogle Formより３日前までに参加登録してください。 ご登録後、会議参加に必要なURLを送付いたします。
Rachel Fewster 氏 (University of Auckland)
Stochastic modelling in ecology: why is it interesting? (ENGLISH)
[ 講演概要 ]
Asia-Pacific Seminar in Probability and Statistics https://sites.google.com/view/apsps/home
The ecological sciences offer rich pickings for stochastic modellers. There is currently an abundance of new technologies for monitoring wildlife and biodiversity, for which no practicable data-analysis methods exist. Often, modelling approaches that are motivated by a specific problem with relatively narrow focus can turn out to have surprisingly broad application elsewhere. As the generality of the problem structure becomes clear, this can also motivate new statistical theory.
I will describe some ecological modelling scenarios that have led to interesting developments from methodological and theoretical perspectives. As time allows, these will include: saddlepoint approximations for dealing with data corrupted by non-invertible linear transformations; information theory for assuring that it is a good idea to unite data from multiple sources; and methods for dealing with so-called 'enigmatic' data from remote sensors, involving a blend of ideas from point processes, queuing theory, and trigonometry. All scenarios will be generously illustrated with pictures of charismatic wildlife.
This talk covers joint work with numerous collaborators, especially Joey Wei Zhang, Mark Bravington, Peter Jupp, Jesse Goodman, Martin Hazelton, Godrick Oketch, Ben Stevenson, David Borchers, Paul van Dam-Bates, and Stephen Marsland.
[ 参考URL ]Asia-Pacific Seminar in Probability and Statistics https://sites.google.com/view/apsps/home
The ecological sciences offer rich pickings for stochastic modellers. There is currently an abundance of new technologies for monitoring wildlife and biodiversity, for which no practicable data-analysis methods exist. Often, modelling approaches that are motivated by a specific problem with relatively narrow focus can turn out to have surprisingly broad application elsewhere. As the generality of the problem structure becomes clear, this can also motivate new statistical theory.
I will describe some ecological modelling scenarios that have led to interesting developments from methodological and theoretical perspectives. As time allows, these will include: saddlepoint approximations for dealing with data corrupted by non-invertible linear transformations; information theory for assuring that it is a good idea to unite data from multiple sources; and methods for dealing with so-called 'enigmatic' data from remote sensors, involving a blend of ideas from point processes, queuing theory, and trigonometry. All scenarios will be generously illustrated with pictures of charismatic wildlife.
This talk covers joint work with numerous collaborators, especially Joey Wei Zhang, Mark Bravington, Peter Jupp, Jesse Goodman, Martin Hazelton, Godrick Oketch, Ben Stevenson, David Borchers, Paul van Dam-Bates, and Stephen Marsland.
https://docs.google.com/forms/d/e/1FAIpQLSf05P9fCZ5Wkasc7clW1XBpkeONPSjPKuCkNYb3oIqnOAu5Mg/viewform
