Department of Statistics


Software development

Software development is an important part of our research and teaching activities. Activities range from a few short lines to automate a few tests or software to help teach, to more extensive simulations and fully featured statistical suites.

The R Project


Rlogo

Statistical programming language R is our best-known product. The R Project, first developed by Ross Ihaka and Robert Gentleman, is now used daily by thousands of people worldwide and being maintained by a cast of hundreds.

The R Project

The R software is easily extended with packages, which may be found on [CRAN]. Within our Department we have developed a number of these packages.

The Comprehensive R Archive Network
R packages we have developed

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Statistical Education Tools


Stat_Ed_Tools

Statistical Educational Tools are being developed by Maxine Pfannkuch, Stephanie Budgett, Chris Wild, Geofferey Pritchard and others. Few of them are listed below:

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PhyML and PhyTime


Work on genetics requires sophisticated software to answer questions quickly. PhyML, a software that estimates maximum likelihood phylogenies from alignments of nucleotide or amino acid sequences, was written by Stéphane Guindon and Olivier Gascuel.

PhyML -  https://github.com/stephaneguindon/phyml

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CensusAtSchool New Zealand


census

Schools benefit from the curriculum and software we have helped develop as part of CensusAtSchool New Zealand and from the work done by our statistical education researchers.

Sophisticated software, powered by the R language and environment for statistical computing, allows investigation of data through a web browser. Similar software is very expensive; we provide it for free to anyone with an internet connection. Because it runs via the web there is no need to install anything.

Find more information about CensusAtSchool New Zealand

 

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iNZight


inzight_transp

inzight is a desktop (Windows, Mac and Linux ) data visualisation and analysis system designed to make data exploration quick and easy. It extends from simple graphics and analyses to  flexible multivariate visualisation capabilities and supports 3D graphics, maps, time series, and multivariable regression analysis.

To get iNZight for Mac, Windows, Linux: https://www.stat.auckland.ac.nz/~wild/iNZight/index.php

inzight lite is an online version of the software, which requires only access to the internet and a latest version of a modern web browser, thus making it accessible to a wider range of users and devices.

 

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Visual inference Tools (VIT)


vit

VIT is a collection of software modules for use in teaching and learning experiences aimed at developing the core concepts of statistical inference. VIT is desktop software that ships with inzight.

An online version VITonline is at https://www.stat.auckland.ac.nz/~wild/VITonline/ .

 

 

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Conservation - IT Tools


cl-stat-rodent-invasion-project
catchIT

We are developing a range of tools to support community conservation initiatives and conservation management in New Zealand.

  •  CatchIT
    • It is a one-stop shop for data management and analysis for community pest control projects. We store and secure data from trap-lines, bait-lines, tracking tunnels, and from wax tags and other lures. Volunteers or admin can log in and enter their catch records to our database online. We can also upload historical trapping records through Excel spreadsheets. We provide a suite of maps, graphics, animations, and analyses to display trapping results and bait uptake. We are continually developing new outputs and can respond to requests. We aim to help engage and motivate community volunteers by seeing their data come to life on the screen.
    • More about the project, including example graphics and demo videos, can be found at our website: https://www.stat.auckland.ac.nz/~fewster/CatchIT/ 
    • CatchIT is hosted by the University of Auckland and has been sponsored by TFBIS, WWF, RSNZ, BeSTGRID, and the University of Auckland.

     

  • Rapid eradication assessment (REA)
    • It is a statistical tool for eradication managers monitoring the outcome of a recent small mammal eradication. Users enter a GIS shape file for the island and a list of monitoring device locations, as well as other parameters on the monitoring framework and biology of the target species. Managers can then quickly calculate the probability that eradication has been successful following one or more follow-up monitoring expeditions, rather than waiting the standard two yaer to confirm eradication.
    • The user interface is simple and includes an example eradication monitoring exercise. Results are presented as both summary output (the probability of successful eradication with confidence intervals) and graphically.
    • The REA interface was recently developed and will continue to be developed for future functionality and improvements.
    • Read more on:

       

       

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Calculate Wind fetch


nz_fetch

Wind fetch is an important measurement in coastal applications. It provides a measurement for the unobstructed length of water over which wind from a certain direction can blow over. The higher the wind fetch from a certain direction, the more energy is imparted onto the surface of the water resulting in a larger sea state. Therefore, the larger the fetch, the larger the exposure to wind and the more likely the site experiences larger sea states. This application allows you to automatically and objectively calculate the wind fetch for marine locations anywhere on Earth.

Use the application or standalone R package - fetchR here

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