Wednesday, 20 November 2013
An interview with Noel Cressie
An interview with Distinguished Professor Noel Cressie of the University
of Wollongong, a big name in spatial statistics, advocate of
hierarchical modeling in ecology, and author of a key reference text in
spatial statistics, and more recently "Statistics for Spatio-temporal
data" with Chris Wikle; we discuss all of these topics.
Thursday, 19 September 2013
Dr Renner it is
Ian Renner has been officially awarded his PhD for a thesis titled "Advances in
Presence-Only Methods in Ecology". Congratulations Ian! Now to publish some of those chapters..
Tuesday, 3 September 2013
Interview with Trevor Hastie
An interview with Trevor Hastie, The John A. Overdeck Professor of Mathematical Sciences
at Stanford, for Methods in Ecology and Evolution. We discuss a recent response he wrote to a 2012 MEE paper by Andy Royle et al.
at Stanford, for Methods in Ecology and Evolution. We discuss a recent response he wrote to a 2012 MEE paper by Andy Royle et al.
Tuesday, 18 June 2013
TIES conference in Anchorage, Alaska
Congratulations to Francis Hui who battled 22 hours of sunlight a day, got within meters of a wild moose, saw a cool ice glacier and earned an honorable mention in the student category for his presentation: "Variable selection in multi-species mixture modeling" at the 23rd annual International Environmetrics Society conference in Anchorage, Alaska, USA, 2013. Well done!
Friday, 10 May 2013
Eco-Stats now on Twitter, and Facebook
Eco-Stats is now on twitter, @ecostats
and on Facebook, https://www.facebook.com/ecostats.unsw
God help us all.
and on Facebook, https://www.facebook.com/ecostats.unsw
God help us all.
Saturday, 27 April 2013
Rumble in the Jungle - SAMs vs separate species SDMs
Our manuscript, To mix or not to mix: comparing the predictive performance of mixture models versus separate species distribution models, has just been accepted by Ecology. A preprint is now available at http://www.esajournals.org/doi/abs/10.1890/12-1322.1
In it, we compare the predictive performance of separate species SDMs and Species Archetype Models (SAMs) on several multi-species datasets. SAMs is a recently developed statistical tool that clusters species based on their environmental response into archetypal response groups. To see who wins the bout, SAMs or separate species SDMs, view the paper!
In it, we compare the predictive performance of separate species SDMs and Species Archetype Models (SAMs) on several multi-species datasets. SAMs is a recently developed statistical tool that clusters species based on their environmental response into archetypal response groups. To see who wins the bout, SAMs or separate species SDMs, view the paper!
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