Eco-Stats Lab April 2014: Block Bootstrap

In this weeks lab we learn about the block bootstrap. A non parametric way to deal with spatial auto correlation in your data and still make valid inferences.

Bootstrap Recap

•Bootstrapping allows us to find the unknown distribution of a statistic by resampling the original data (with replacement) and recalculating the statistic many times.

•Hence we can calculate p-values and standard errors of things we don’t know the distribution of.

•Assumptions: observations are independent and identically distributed ("iid")

 But you can't use an iid bootstrap when data are spatially correlated

David Warton wins Young Investigator Award from American Statistical Association

We're all very proud that David has won another major award this year, this one the Young Investigator Award from the American Statistical Association Section on Statistics and the Environment. He's been recognized internationally for outstanding contributions to the development of methods, issues, concepts, applications, and initiatives in environmental statistics by a young statistician. And we quite agree.

Well done David!

More on the school website:
https://www.maths.unsw.edu.au/news/2014-04/david-warton-young-investigator-award

Eco-Stats Lab, March 2014 - Measurement Error modeling using SIMEX

Measurement Error modeling using SIMEX

Date: 28th March 2-3pm
Venue: Computer Lab Room 640

Slides:

Measurement Error Modeling

• Measurement error or error-in-variables arises whenever we have imprecise measurements on our predictor variables (or covariates).
• If X is the true covariate and U is the measurement error, then what we observe is
  W = X + U:
• In a simple regression, we usually assume that our covariates are measured precisely or they represent the true covariate values quite well. But what happens to our estimates if our covariates have measurement error?

Eco-Stats Lab, Feb 2014 - SMATR

The SMATR package (Standardised Major Axis estimation and Testing Routines) is designed for when you are fitting lines and:
- you are primarily interested in the slope (rather than significance or strength of association)
- the problem is symmetric, i.e. you could happily swap which variable is on which axis without changing the meaning of what you are doing.  Or put another way, rather than predicting Y from X (regression), you have a pair of Y variables (Y1 and Y2) and you want to see how they are related to each other.

This situation commonly arises in allometry (the study of how one size variable scales against another), this is the main place these methods are useful in ecology.

MAXENT equivalence paper rated "Exceptional" on Faculty of 1000

The first paper from Ian Renner's PhD thesis, "Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology", has been rated by the Faculty of 1000.  F1000 is a post-publication peer review website that highlights noteworthy articles from the scientific literature, especially biology and medicine articles.  Renner & Warton (2013) received the top rating (three stars, "Exceptional"), which we are pretty chuffed about.  For details, see the review at http://f1000.com/prime/718270492

Eco-Stats Paper of the Year, 2013

We just had our second annual paper of the year competition, highlighting papers that made an impression to UNSW Eco-Stats researchers over the previous year.  Papers were supposed to be in print in 2013, but this was interpreted generously. And the nominees are...

Ecostats Workshop - Mixture Models

To all those coming to the UNSW Ecostats workshop on Mixture models,

Date: 31st January 2-3pm
Venue: Computer Lab Room 640...somewhere in Sydney =D
Topic: A very very short introduction to mixture models with a very very short taste of how to implement them in R
MC: Francis Hui (PhD student; UNSW School of Maths and Stats)

Please note that this blog is NOT to be used for indicating that you want to attend. That should have been done via the email sent out by Richard Kingsford earlier.

Unfortunately, blogger does not allow one to attach thing that aren't videos or images, so I've instead provided links to the material I shall be using.

Slides: https://www.dropbox.com/s/0ibha7nk2u8k22u/minilecturev1.pdf?dl=0
R script: https://www.dropbox.com/s/kg3bcyt65ec6nhl/scripts_cutdown.R?dl=0



Thank you.

Yours non-significantly,
FH