Comparison of Two Methods for Caluculating the Partition Functions of Various Spatial Statistical Models

Likelihood computation in spatial statistics requires accurate and efficient calculation of the normalizing constant (i.e. partition function) of the Gibbs distribution of the model. Two available methods to calculate the normalizing constant by Markov chain Monte Carlo methods are compared by simulation experiments for an Ising model, a Gaussian Markov field model and a pairwise interaction point field model.

Statistical models for cancer screening

This paper reviews the application of statistical models to planning and evaluating cancer screening programmes. Models used to analyse screening strategies can be classified as either surface models, which consider only those events which can be directly observed such as disease incidence, prevalence or mortality, or deep models, which incorporate hypotheses about the disease process that generates the observed events. This paper focuses on the latter type. These can be further classified as analytic models, which use a model of the disease to derive direct estimates of characteristics of the screening procedure and its consequent benefits, and simulation models, which use the disease model to simulate the course of the disease in a hypothetical population with and without screening and derive measures of the benefit of screening from the simulation outcomes. The main approaches to each type of model are described and an overview given of their historical development and strengths and weaknesses. A brief review of fitting and validating such models is given and finally a discussion of the current state of, and likely future trends in, cancer screening models is presented.

Generalized pseudo-likelihood estimates for markov random fields on lattice

In this paper we generalize Besag's pseudo-likelihood function for spatial statistical models on a region of a lattice. The correspondingly defined maximum generalized pseudo-likelihood estimates (MGPLEs) are natural extensions of Besag's maximum pseudo-likelihood estimate (MPLE). The MGPLEs connect the MPLE and the maximum likelihood estimate. We carry out experimental calculations of the MGPLEs for spatial processes on the lattice. These simulation results clearly show better performances of the MGPLEs than the MPLE, and the performances of differently defined MGPLEs are compared. These are also illustrated by the application to two real data sets.

Women's psychosocial well-being following a major life transition

Some women are devastated by divorce, while others learn from the experience. In-depth interviews with sole-parenting women yielded themes that were then assessed using structured questionnaires. Statistical models showed that psychological adjustment and physical well-being related more strongly to psychological factors, such as sense of coherence, than to situational variables.

Stable isotope-based community metrics as a tool to identify patterns in food web structure in east African estuaries

1.Quantitative tools to describe biological communities are important for conservation and ecological management. The analysis of trophic structure can be used to quantitatively describe communities. Stable isotope analysis is useful to describe trophic organization, but statistical models that allow the identification of general patterns and comparisons between systems/sampling periods have only recently been developed. 2.Here, stable isotope-based Bayesian community-wide metrics are used to investigate patterns in trophic structure in five estuaries that differ in size, sediment yield and catchment vegetation cover (C3/C4): the Zambezi in Mozambique, the Tana in Kenya and the Rianila, the Betsiboka and Pangalanes Canal (sampled at Ambila) in Madagascar. 3.Primary producers, invertebrates and fish of different trophic ecologies were sampled at each estuary before and after the 2010–2011 wet season. Trophic length, estimated based on δ15N, varied between 3·6 (Ambila) and 4·7 levels (Zambezi) and did not vary seasonally for any estuary. Trophic structure differed the most at Ambila, where trophic diversity and trophic redundancy were lower than at the other estuaries. Among the four open estuaries, the Betsiboka and Tana (C4-dominated) had lower trophic diversity than the Zambezi and Rianila (C3-dominated), probably due to the high loads of suspended sediment, which limited the availability of aquatic sources. 4.There was seasonality in trophic structure at Ambila and Betsiboka, as trophic diversity increased and trophic redundancy decreased from the prewet to the postwet season. For Ambila, this probably resulted from the higher variability and availability of sources after the wet season, which allowed diets to diversify. For the Betsiboka, where aquatic productivity is low, this was likely due to a greater input of terrestrial material during the wet season. 5.The comparative analysis of community-wide metrics was useful to detect patterns in trophic structure and identify differences/similarities in trophic organization related to environmental conditions. However, more widespread application of these approaches across different faunal communities in contrasting ecosystems is required to allow identification of robust large-scale patterns in trophic structure. The approach used here may also find application in comparing food web organization before and after impacts or monitoring ecological recovery after rehabilitation.

Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion

Statistical time series methods have proven to be a promising technique in structural health monitoring, since it provides a direct form of data analysis and eliminates the requirement for domain transformation. Latest research in structural health monitoring presents a number of statistical models that have been successfully used to construct quantified models of vibration response signals. Although a majority of these studies present viable results, the aspects of practical implementation, statistical model construction and decision-making procedures are often vaguely defined or omitted from presented work. In this article, a comprehensive methodology is developed, which essentially utilizes an auto-regressive moving average with exogenous input model to create quantified model estimates of experimentally acquired response signals. An iterative self-fitting algorithm is proposed to construct and fit the auto-regressive moving average with exogenous input model, which is capable of integrally finding an optimum set of auto-regressive moving average with exogenous input model parameters. After creating a dataset of quantified response signals, an unlabelled response signal can be identified according to a 'closest-fit' available in the dataset. A unique averaging method is proposed and implemented for multi-sensor data fusion to decrease the margin of error with sensors, thus increasing the reliability of global damage identification. To demonstrate the effectiveness of the developed methodology, a steel frame structure subjected to various bolt-connection damage scenarios is tested. Damage identification results from the experimental study suggest that the proposed methodology can be employed as an efficient and functional damage identification tool. © The Author(s) 2014.

Optimal fire histories for biodiversity conservation

Fire is used as a management tool for biodiversity conservation worldwide. A common objective is to avoid population extinctions due to inappropriate fire regimes. However, in many ecosystems, it is unclear what mix of fire histories will achieve this goal. We determined the optimal fire history of a given area for biological conservation with a method that links tools from 3 fields of research: species distribution modeling, composite indices of biodiversity, and decision science. We based our case study on extensive field surveys of birds, reptiles, and mammals in fire-prone semi-arid Australia. First, we developed statistical models of species' responses to fire history. Second, we determined the optimal allocation of successional states in a given area, based on the geometric mean of species relative abundance. Finally, we showed how conservation targets based on this index can be incorporated into a decision-making framework for fire management. Pyrodiversity per se did not necessarily promote vertebrate biodiversity. Maximizing pyrodiversity by having an even allocation of successional states did not maximize the geometric mean abundance of bird species. Older vegetation was disproportionately important for the conservation of birds, reptiles, and small mammals. Because our method defines fire management objectives based on the habitat requirements of multiple species in the community, it could be used widely to maximize biodiversity in fire-prone ecosystems. © 2014 Society for Conservation Biology.

Visualization of HIV-1 interactions with penile and foreskin epithelia: clues for female-to-male HIV transmission

To gain insight into female-to-male HIV sexual transmission and how male circumcision protects against this mode of transmission, we visualized HIV-1 interactions with foreskin and penile tissues in ex vivo tissue culture and in vivo rhesus macaque models utilizing epifluorescent microscopy. 12 foreskin and 14 cadaveric penile specimens were cultured with R5-tropic photoactivatable (PA)-GFP HIV-1 for 4 or 24 hours. Tissue cryosections were immunofluorescently imaged for epithelial and immune cell markers. Images were analyzed for total virions, proportion of penetrators, depth of virion penetration, as well as immune cell counts and depths in the tissue. We visualized individual PA virions breaching penile epithelial surfaces in the explant and macaque model. Using kernel density estimated probabilities of localizing a virion or immune cell at certain tissue depths revealed that interactions between virions and cells were more likely to occur in the inner foreskin or glans penis (from local or cadaveric donors, respectively). Using statistical models to account for repeated measures and zero-inflated datasets, we found no difference in total virions visualized at 4 hours between inner and outer foreskins from local donors. At 24 hours, there were more virions in inner as compared to outer foreskin (0.0495 +/- 0.0154 and 0.0171 +/- 0.0038 virions/image, p = 0.001). In the cadaveric specimens, we observed more virions in inner foreskin (0.0507 +/- 0.0079 virions/image) than glans tissue (0.0167 +/- 0.0033 virions/image, p<0.001), but a greater proportion was seen penetrating uncircumcised glans tissue (0.0458 +/- 0.0188 vs. 0.0151 +/- 0.0100 virions/image, p = 0.099) and to significantly greater mean depths (29.162 +/- 3.908 vs. 12.466 +/- 2.985 μm). Our in vivo macaque model confirmed that virions can breach penile squamous epithelia in a living model. In summary, these results suggest that the inner foreskin and glans epithelia may be important sites for HIV transmission in uncircumcised men.

Exploring spatiotemporal trends in commercial fishing effort of an abalone fishing zone: a GIS-based hotspot model

Assessing patterns of fisheries activity at a scale related to resource exploitation has received particular attention in recent times. However, acquiring data about the distribution and spatiotemporal allocation of catch and fishing effort in small scale benthic fisheries remains challenging. Here, we used GIS-based spatio-statistical models to investigate the footprint of commercial diving events on blacklip abalone (Haliotis rubra) stocks along the south-west coast of Victoria, Australia from 2008 to 2011. Using abalone catch data matched with GPS location we found catch per unit of fishing effort (CPUE) was not uniformly spatially and temporally distributed across the study area. Spatial autocorrelation and hotspot analysis revealed significant spatiotemporal clusters of CPUE (with distance thresholds of 100's of meters) among years, indicating the presence of CPUE hotspots focused on specific reefs. Cumulative hotspot maps indicated that certain reef complexes were consistently targeted across years but with varying intensity, however often a relatively small proportion of the full reef extent was targeted. Integrating CPUE with remotely-sensed light detection and ranging (LiDAR) derived bathymetry data using generalized additive mixed model corroborated that fishing pressure primarily coincided with shallow, rugose and complex components of reef structures. This study demonstrates that a geospatial approach is efficient in detecting patterns and trends in commercial fishing effort and its association with seafloor characteristics.

The adaptable buffer algorithm for high quantile estimation in non-stationary data streams

The need to estimate a particular quantile of a distribution is an important problem which frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many semi-automatic surveillance analytics systems which detect abnormalities in close-circuit television (CCTV) footage using statistical models of low-level motion features. In this paper we specifically address the problem of estimating the running quantile of a data stream with non-stationary stochasticity when the memory for storing observations is limited. We make several major contributions: (i) we derive an important theoretical result which shows that the change in the quantile of a stream is constrained regardless of the stochastic properties of data, (ii) we describe a set of high-level design goals for an effective estimation algorithm that emerge as a consequence of our theoretical findings, (iii) we introduce a novel algorithm which implements the aforementioned design goals by retaining a sample of data values in a manner adaptive to changes in the distribution of data and progressively narrowing down its focus in the periods of quasi-stationary stochasticity, and (iv) we present a comprehensive evaluation of the proposed algorithm and compare it with the existing methods in the literature on both synthetic data sets and three large 'real-world' streams acquired in the course of operation of an existing commercial surveillance system. Our findings convincingly demonstrate that the proposed method is highly successful and vastly outperforms the existing alternatives, especially when the target quantile is high valued and the available buffer capacity severely limited.

Two maximum entropy-based algorithms for running quantile estimation in nonstationary data streams

The need to estimate a particular quantile of a distribution is an important problem that frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many semiautomatic surveillance analytics systems that detect abnormalities in close-circuit television footage using statistical models of low-level motion features. In this paper, we specifically address the problem of estimating the running quantile of a data stream when the memory for storing observations is limited. We make the following several major contributions: 1) we highlight the limitations of approaches previously described in the literature that make them unsuitable for nonstationary streams; 2) we describe a novel principle for the utilization of the available storage space; 3) we introduce two novel algorithms that exploit the proposed principle in different ways; and 4) we present a comprehensive evaluation and analysis of the proposed algorithms and the existing methods in the literature on both synthetic data sets and three large real-world streams acquired in the course of operation of an existing commercial surveillance system. Our findings convincingly demonstrate that both of the proposed methods are highly successful and vastly outperform the existing alternatives. We show that the better of the two algorithms (data-aligned histogram) exhibits far superior performance in comparison with the previously described methods, achieving more than 10 times lower estimate errors on real-world data, even when its available working memory is an order of magnitude smaller.

Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013

Background: Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0-65·6) in 1990, to 71·5 years (UI 71·0-71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8-48·2) to 54·9 million (UI 53·6-56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased.For women aged 25-39 years and older than 75 years and for men aged 20-49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.

Continuous validation for data analytics systems

From a future history of 2025: Continuous development is common for build/test (continuous integration) and operations (devOps). This trend continues through the lifecycle, into what we call `devUsage': continuous usage validation. In addition to ensuring systems meet user needs, organisations continuously validate their legal and ethical use. The rise of end-user programming and multi-sided platforms exacerbate validation challenges. A separate trend isthe specialisation of software engineering for technical domains, including data analytics. This domain has specific validation challenges. We must validate the accuracy of sta-tistical models, but also whether they have illegal or unethical biases. Usage needs addressed by machine learning are sometimes not speci able in the traditional sense, and statistical models are often `black boxes'. We describe future research to investigate solutions to these devUsage challenges for data analytics systems. We will adapt risk management and governance frameworks previously used for soft-ware product qualities, use social network communities for input from aligned stakeholder groups, and perform cross-validation using autonomic experimentation, cyber-physical data streams, and online discursive feedback.

Evaluation of three daily rainfall generation models for SWAT

The Soil and Water Assessment Tool (SWAT) is a hydrologic model that was developed to predict the long-term impacts of land use change on the water balance of large catchments. Stochastic models are used to generate the daily rainfall sequences needed to conduct long-term, continuous simulations with SWAT. The objective of this study was to evaluate the performances of three daily rainfall generation models. The models evaluated were the modified Daily and Monthly Mixed (DMMm) model, skewed normal distribution (SKWD) model and modified exponential distribution (EXPD) model. The study area was the Woady Yaloak River catchment (306 km2) located in southwest Victoria, Australia. The models were assessed on their ability to preserve annual, monthly and daily statistical characteristics of the historical rainfall and runoff. The mean annual, monthly, and daily rainfall was preserved satisfactorily by the models. The DMMm model reproduced the standard deviation of annual and monthly rainfall better than the SKWD and EXPD models. Overall, the DMMm model performed marginally better than the SKWD model at reproducing the statistical characteristics of the historical rainfall record at the various time scales. The performance of the EXPD model was found to be inferior to the performances of the DMMm and SKWD models. The models reproduced the mean annual, monthly, and daily runoff relatively well, although the DMMm and SKWD models were found to preserve these statistics marginally better than the EXPD model. None of the models managed to reproduce the standard deviation of annual, monthly, and daily runoff adequately.

Benchmarking new statistical techniques in ration-based modelling of corporate collapse

Up until 1979, Multiple Discriminant Analysis (MDA) was the primary multivariate methodological approaches to ratio-based modelling of corporate collapse. However, as new statistical tools became available, researchers started testing them with the primary objective of deriving models that would at least do as good a job as MDA, but that rely on fewer assumptions. Regardless of which methodological approach was chosen, most were compared to MDA. This paper analyses 84 studies on ratio based modelling of corporate collapse over the period 1968 to 2004. The results indicate that when MDA was not the primary methodology it was the benchmark of choice for comparison; thereby, demonstrating its importance as a foundation multivariate methodological approach in signalling corporate collapse.