Approximate Bayesian computation using indirect inference

We present a novel approach for developing summary statistics for use in approximate Bayesian computation (ABC) algorithms by using indirect inference. ABC methods are useful for posterior inference in the presence of an intractable likelihood function. In the indirect inference approach to ABC the parameters of an auxiliary model fitted to the data become the summary statistics. Although applicable to any ABC technique, we embed this approach within a sequential Monte Carlo algorithm that is completely adaptive and requires very little tuning. This methodological development was motivated by an application involving data on macroparasite population evolution modelled by a trivariate stochastic process for which there is no tractable likelihood function. The auxiliary model here is based on a beta–binomial distribution. The main objective of the analysis is to determine which parameters of the stochastic model are estimable from the observed data on mature parasite worms.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

Towards semantic search and inference in electronic medical records : an approach using concept-based information retrieval

For more than a decade research in the field of context aware computing has aimed to find ways to exploit situational information that can be detected by mobile computing and sensor technologies. The goal is to provide people with new and improved applications, enhanced functionality and better use experience (Dey, 2001). Early applications focused on representing or computing on physical parameters, such as showing your location and the location of people or things around you. Such applications might show where the next bus is, which of your friends is in the vicinity and so on. With the advent of social networking software and microblogging sites such as Facebook and Twitter, recommender systems and so on context-aware computing is moving towards mining the social web in order to provide better representations and understanding of context, including social context. In this paper we begin by recapping different theoretical framings of context. We then discuss the problem of context- aware computing from a design perspective.

PySSM : a Python module for Bayesian inference of linear Gaussian state space models

PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

Towards semantic search and inference in electronic medical records : an approach using concept-based information retrieval

Background This paper presents a novel approach to searching electronic medical records that is based on concept matching rather than keyword matching. Aim The concept-based approach is intended to overcome specific challenges we identified in searching medical records. Method Queries and documents were transformed from their term-based originals into medical concepts as defined by the SNOMED-CT ontology. Results Evaluation on a real-world collection of medical records showed our concept-based approach outperformed a keyword baseline by 25% in Mean Average Precision. Conclusion The concept-based approach provides a framework for further development of inference based search systems for dealing with medical data.

Emergent innovation through the co-evolution of informal and formal media economies

Well-established distinctions between amateur and professional are blurring as the impact of social media, changes in cultural consumption, and crises in copyright industries’ business models are felt across society and economy. I call this the increasingly rapid co-evolution of the formal market and informal household sectors and analyse it through the concept of ‘social network markets’ – individual choices are made on the basis of other’s choices and such networked preferencing is enhanced by the growing ubiquity of social media platforms. This may allow us better to understand sources of disruption and innovation in audiovisual production and distribution in wealthy Western markets which are as significant as those posed by informal practices outside the West. I examine what is happening around the monetization and professionalization of online video (YouTube, for example) and the socialization of professional production strategies (transmedia, for example) as innovation from the margins.

The governance of inter-organisational decision-making : understanding the impacts of informal networks on formal decision-making regimes in the Brisbane Airport region

Airports and cities inevitably recognise the value that each brings the other; however, the separation in decision-making authority for what to build, where, when and how provides a conundrum for both parties. Airports often want a say in what is developed outside of the airport fence, and cities often want a say in what is developed inside the airport fence. Defining how much of a say airports and cities have in decisions beyond their jurisdictional control is likely to be a topic that continues so long as airports and cities maintain separate formal decision-making processes for what to build, where, when and how. However, the recent Green and White Papers for a new National Aviation Policy have made early inroads to formalising relationships between Australia’s major airports and their host cities. At present, no clear indication (within practice or literature) is evident to the appropriateness of different governance arrangements for decisions to develop in situations that bring together the opposing strategic interests of airports and cities; thus leaving decisions for infrastructure development as complex decision-making spaces that hold airport and city/regional interests at stake. The line of enquiry is motivated by a lack of empirical research on networked decision-making domains outside of the realm of institutional theorists (Agranoff & McGuire, 2001; Provan, Fish & Sydow, 2007). That is, governance literature has remained focused towards abstract conceptualisations of organisation, without focusing on the minutia of how organisation influences action in real-world applications. A recent study by Black (2008) has provided an initial foothold for governance researchers into networked decision-making domains. This study builds upon Black’s (2008) work by aiming to explore and understand the problem space of making decisions subjected to complex jurisdictional and relational interdependencies. That is, the research examines the formal and informal structures, relationships, and forums that operationalise debates and interactions between decision-making actors as they vie for influence over deciding what to build, where, when and how in airport-proximal development projects. The research mobilises a mixture of qualitative and quantitative methods to examine three embedded cases of airport-proximal development from a network governance perspective. Findings from the research provide a new understanding to the ways in which informal actor networks underpin and combine with formal decision-making networks to create new (or realigned) governance spaces that facilitate decision-making during complex phases of development planning. The research is timely, and responds well to Isett, Mergel, LeRoux, Mischen and Rethemeyer’s (2011) recent critique of limitations within current network governance literature, specifically to their noted absence of empirical studies that acknowledge and interrogate the simultaneity of formal and informal network structures within network governance arrangements (Isett et al., 2011, pp. 162-166). The combination of social network analysis (SNA) techniques and thematic enquiry has enabled findings to document and interpret the ways in which decision-making actors organise to overcome complex problems for planning infrastructure. An innovative approach to using association networks has been used to provide insights to the importance of the different ways actors interact with one another, thus providing a simple yet valuable addition to the increasingly popular discipline of SNA. The research also identifies when and how different types of networks (i.e. formal and informal) are able to overcome currently known limitations to network governance (see McGuire & Agranoff, 2011), thus adding depth to the emerging body of network governance literature surrounding limitations to network ways of working (i.e. Rhodes, 1997a; Keast & Brown, 2002; Rethemeyer & Hatmaker, 2008; McGuire & Agranoff, 2011). Contributions are made to practice via the provision of a timely understanding of how horizontal fora between airports and their regions are used, particularly in the context of how they reframe the governance of decision-making for airport-proximal infrastructure development. This new understanding will enable government and industry actors to better understand the structural impacts of governance arrangements before they design or adopt them, particularly for factors such as efficiency of information, oversight, and responsiveness to change.

Shut up and write! Facilitating informal learning in doctoral candidature

Doctoral candidates spend at least 2/3 of their degree outside of structured classroom instruction; most of their learning and writing takes place in their own time. Providing research degree candidates with writing help during their degree study is difficult. Candidates come into their degree with widely varying needs and levels of experience. Course work might seem to offer a way to create parity, but, according to the Australian Qualification Framework, mandated coursework can only occupy 1⁄3 of the degree

Between formal and informal : the shakeout in China’s online video industry

While a rich body of literature in television and film studies and media policy studies has tended to focus on the media activities in the formal sector, we know much less about informal media activities, its influence on state policies, as well as the dynamics between the formal and the informal sectors. This article examines these issues with reference to a particularly revealing period following a large-scale government crackdown on peer-to-peer video sharing sites in China in 2008. By analyzing the aim and consequences of the state action, I point to the counter-productive effect in terms of cultural loss and the resurgence of offline piracy; and show the positive impact on forcing the informal into the formal sector, and pressuring the formal to innovate. Meanwhile, an increasing rapprochement between professional and user-created content leads to a new relationship between formal and informal sectors. This case demonstrates the importance of considering the dynamics between the two sectors. It also offers compelling evidence of the role of the informal sector in engendering state action, which in turn impacted on the co-evolution of the formal and the informal sectors.