Australian researchers have made a number of significant contributions to the science of ecological toxicity (ecotox) testing. A significant development was the generalisation of the method proposed by Aldenberg and Slob (1993) for setting confidence limits on a hazardous concentration obtained from a species sensitivity distribution (SSD). More recently, one of our CSIRO colleagues, Shao (2000) suggested the use of the Burr Type III distribution as a more flexible approach to SSD modelling. The methodology was ultimately embodied in a software tool called BurrliOZ developed by CSIRO (http://www.cmis.csiro.au/envir/burrlioz/). While no system or approach to setting protective environmental concentrations is perfect, these statistical extrapolation method has proven to be reasonably robust. This project, in order to provide better user interface, will package the functions developed in Shao (2000) into an R package, and provide Web-based interface for end users to estimate SSD and store the data uploaded for the Web service.
- Package into and test an R package based on existing R code related with Burr Type III distribution
- Implement a Web interface to provide a service for estimating SSD for variouis end users. There are a range of ways that R code can be interfaced via the web (http://cran.r-project.org/doc/FAQ/R-FAQ.html#R-Web...).
- Familiarity with the script language, ideally, R computing language
- Basics of statistical computation like maximum likelihood estimation
- R free software for Statistical Computing
- Aldenberg T and Slob W. 1993. Confidence limits for hazardous concentrations based on logistically distributed NOEC toxicity data. Ecotoxicology and Environmental Safety 25, 48-63.
- Shao Q. 2000. Estimation for hazardous concentrations based on NOEC toxicity data: an alternative approach. Environmetrics 11, 583-595.
- OECD. 2006. Current Approaches in the Statistical a analysis of Ecotoxicology Data: A Guidance to Application. Series on Testing and Assessment, No. 54. Environmental Health and Safety Publications, Series on testing and assessment. ENV/JM/MONO(2006)18.
- CSIRO (www.csiro.au), as Australiaâ€™s national science agency is one of the largest and most diverse research agencies in the world. It operates large multi-disciplinary research teams. By doing a project with CSIRO you will have access to world class facilities and be able to work alongside CSIRO scientists while you are enjoying generous personal development and learning opportunities.
- Software package development experience
- Stronger R skills, that will be valuable for future statistical data analysis or data mining
- Real world problem solving;