Potential Projects

These project descriptions are all pitched at honours level. Starred projects are also suitable for consideration as the starting point of a Ph.D. Data analysis will be done using R, and reporting using L^ATEX!

Inventory sampling intensity

with Glen Rivers of HVP. HVP Plantation undertakes inventory of stands of plantation trees. The current sampling intensity is 1 plot per 4 ha across all inventory types. The project would investigate the impact of using different sampling intensities across the inventory types. It may well be more cost efficient to decrease sampling of younger age stands and increase it for pre harvest inventory without increasing the cost of the annual inventory program. The student would have access to existing inventory data and would be able to design and test several sampling intensity options. HVP would provide contract inventory crews to undertake any additional sampling. HVP would provide all equipment and pay for accommodation and meals outside of Melbourne if the student is required to travel. HVP would also provide a stipend to undertake the project.

Application of alternative sampling techniques

with Glen Rivers of HVP. HVP Plantations currently use the MARVL (The Method for Assessment of Recoverable Volume by Logs type, Deadman and Goulding (NZFRI),1978) methodology to quantify plantation tree and stand parameters. This method uses a combination of fixed area circular `primary' plots and basal area sweep `secondary' plots. Stem characteristics of each stem in a plot are `cruised' and are used to predict product out turn. This project would look at alternate inventory techniques, eg importance sampling, considering the accuracy of technique, ease of implementation (field and office) and the cost as compared to the existing MARVL inventory. The student would have access to existing inventory data and would be able to design and test several sampling techniques and intensity scenarios. HVP would provide contract inventory crews to undertake sampling. HVP would provide all equipment and pay for accommodation and meals outside of Melbourne if the student is required to travel. HVP would also provide a stipend to undertake the project.

Watershed Modelling *

with Dr Patrick Lane and Dr Gary Sheridan of ILFR, University of Melbourne. The project will address the data and infrastructure needs for the construction and interpretation of models that will predict the risk of impotable water resulting from bushfire and flooding in Melbourne's catchments. This project will lean heavily upon simulation and modelling.

Large-Scale Forest Data *

with Dr Patrick Baker of Monash University. We have access to a large forest database from Thailand, comprising a single 50 ha forest plot. In 1994, 1999, and 2004, each tree on the plot was measured, which involved recording its species, diameter at 1.3 m, and location. The database comprises 90 to 100 thousand trees for each measurement, with about 300 species. There was a substantial fire in 1998. This project will focus on the development of ecologically coherent statistical models of tree growth and mortality, and an assessment of different techniques for exploring the similarities of different species. This project will lean heavily upon review, data manipulation, and modelling, and should lead to a publication.

Timing of Treatment Intervention

with Martin Ashdown and others. An innovative recent theory for cancer treatment suggests that the timing of treatment, relative to the behaviour of the immune system, could affect treatment success. This project focuses on the problem of modeling possibly cyclic data with very small samples (eg $n = 6$). The goal is to detect the timing of the next peak, and some other parameters may be necessary, but are nuisances! This project will lean heavily upon simulation and programming.

Seed Dispersal

with Professor Roger Cousens. Dispersal is a critical process in invasions by exotic species and in the maintenance of structure within plant and animal communities. A large number of studies in recent years have modelled the rate of spread and pattern within such populations. However, most of these models make arbitrary assumptions about the pdf of dispersal distances. We have one of the most detailed data sets for dispersal: we have mapped x,y coordinates of fruits on the ground after dispersal and x,y,z coordinates of fruits on plants prior to dispersal in wild radish (an agricultural weed). The usual approach is to consider the distances of all dispersed pods from the centre of the plant. However, seeds on the outermost branches of a plant may drop straight to the ground: their dispersal distance is much less than their distance from the plant's centre. Can we estimate the parameters of a pdf for dispersal distance from these data with respect to their point of origin within the parent plant's canopy? What is the most appropriate function to use for this? This project will lean heavily upon simulation and programming, and should lead to a publication.

Environmental Monitoring 1

with Professor David Fox and others. The project focuses on the problem of monitoring where the desired conclusion is non-occurrence. How much can be said about the presence of a biotum of interest if you don't find it at all? And, how can distinct sources of information, with different provenances and spatial coverages, be welded together to an overall statement? This project will lean heavily upon review, simulation and modelling, and should lead to a publication.

Big BAF

A new forest inventory technique has been recently introduced, catchily entitled Big-BAF. Data from such an inventory are hierarchical, and as yet, there seems to be little agreement as to the best way to analyse them. Heuristic evidence suggests that Big-BAF is more efficient than its predecessor VBAR, but the conditions under which it will be true have not yet been explored. We have access to several suitable (large) forestry databases. This project will lean heavily upon simulation and programming, and should lead to a publication.

Search engines

are a useful tool of the Internet. Key marketing features for search engines are the index size (the number of unique pages that the engine has indexed) and timeliness (how up to date is the index). This project will explore experimental design and sampling techniques for estimating and comparing the timeliness and size of the indexes. Using such indicators, this project will apply statistical techniques to quantitatively compare several search engines, such as Sensis, MSN, Yahoo!, and Google.

Critical Period Analysis *

is a new technique that is sometimes used in agriculture to try to discern optimal weed-control strategies. This requires fitting two models to experimental data and estimating where the models cross, and how far apart their asymptotes are. This project considers developments on a recent approach to this problem using maximum likelihood and segmented regression, and would involve fitting models using the EM algorithm.

Methods of Inference

Statistical inference is not a monolith. There are at least three distinct approaches to statistical inference that support flourishing communities of scientists and decision-makers, and several more in niche areas. A number of these approaches have become established in only the last decade or so. This project will survey the range of statistical inference strategies, identifying the common points and differences, and then apply them to some straightforward modelling problems for estimation and inference: e.g. estimating a mean, regression parameters, analysis of variance, etc. Key to the outcome will be identifying the conceptual underpinnings of the inference: what it is necessary to assume, what it is necessary to believe, and so on. The tools used will be R and the argument mapping software called Reason!able. The outcome will be a comparative survey of inference strategies and tools and an R package to implement them in simple modelling problems. This project will focus on reading, review, and interpretation.

Ecological Sampling and Estimation *

with Dr Patrick Baker of Monash University. In ecological studies it is often of interest to be able to estimate the age of the oldest tree in a forest. This turns out to be a sampling problem with numerous facets. This project will look at the application of experimental design and hierarchical extreme-value distributions to the problem.

Environmental Monitoring 2 *

with Rob Goudey, of the Victorian EPA. Monitoring and assessing environmental events requires a translation from a biological effect to an abstract model, fitting the model, and interpreting its parameter estimates in the context of an asymmetric loss function. The EPA of Victoria wishes to develop models and procedures that will connect toxicity information for specific species to a biological event model, with sparse data, in order to be able to establish guidelines for action. The guidelines will alert the EPA that, for example, the probability of a toxic episode has become unacceptably high. The current strategy uses percentile cutoffs, but the nominated rank and the cutoff are arbitrary.