Bayesian emulation for optimization in multi-step portfolio decisions

We discuss the Bayesian emulation approach to computational solution of multi-step portfolio studies in financial time series. "Bayesian emulation for decisions" involves mapping the technical structure of a decision analysis problem to that of Bayesian inference in a purely synthetic "emulating" statistical model. This provides access to standard posterior analytic, simulation and optimization methods that yield indirect solutions of the decision problem. We develop this in time series portfolio analysis using classes of economically and psychologically relevant multi-step ahead portfolio utility functions. Studies with multivariate currency, commodity and stock index time series illustrate the approach and show some of the practical utility and benefits of the Bayesian emulation methodology.Comment: 24 pages, 7 figures, 2 table

Generalized Bayesian MARS: Tools for Emulating Stochastic Computer Models

The multivariate adaptive regression spline (MARS) approach of Friedman (1991) and its Bayesian counterpart (Francom et al. 2018) are effective approaches for the emulation of computer models. The traditional assumption of Gaussian errors limits the usefulness of MARS, and many popular alternatives, when dealing with stochastic computer models. We propose a generalized Bayesian MARS (GBMARS) framework which admits the broad class of generalized hyperbolic distributions as the induced likelihood function. This allows us to develop tools for the emulation of stochastic simulators which are parsimonious, scalable, interpretable and require minimal tuning, while providing powerful predictive and uncertainty quantification capabilities. GBMARS is capable of robust regression with t distributions, quantile regression with asymmetric Laplace distributions and a general form of "Normal-Wald" regression in which the shape of the error distribution and the structure of the mean function are learned simultaneously. We demonstrate the effectiveness of GBMARS on various stochastic computer models and we show that it compares favorably to several popular alternatives

Marginalised youth, violence and policing: a qualitative study in Recife, Brazil

Few studies have examined the relations between urban marginalised youth and the public security system in the northeast of Brazil. This article addresses this gap in the literature through an examination of youth perceptions of a security programme aimed at reducing violence. It also analyses the effects of this security program by interrogating the hegemonic discourses of state-actors in the region, namely, agents of the criminal justice system. The analysis draws on ethnographic data collected between 2012 and 2016 in Recife, the capital city of the state of Pernambuco in the northeast of Brazil. This approach permits an examination of the nature of new security interventions, and a comparison between two distinct narratives about this new securitisation agenda. One overarching narrative focuses on young people’s vulnerabilities, the other on claims of successful securitisation. An analysis of these narratives widens understandings of the effects and risks of security interventions, contributing to a debate about their impact on young people’s lives and society at large

Network Routing Using the Network Tasking Order, a Chron Approach

This thesis promotes the use of the network tasking order (NTO), in collaboration with the air tasking order (ATO), to optimize routing in Mobile Ad hoc Networks (MANET). The network topology created by airborne platforms is determined ahead of time and network transitions are calculated offline prior to mission execution. This information is used to run maximum multi-commodity flow algorithms offline to optimize network flow and schedule route changes for each network node. These calculations and timely route modifications increases network efficiency. This increased performance is critical to command and control decision making in the battlefield. One test scenario demonstrates near a 100% success rate when route scheduling and splitting network traffic over an emulated MANET compared to Open Shortest Path First (OSPF) which only achieved around a 71% success rate, and Mesh Made Easy (MME) which achieved about 50% success. Another test scenario demonstrates that the NTO can experience degradation due to schedule delay. Overall, if executed and planned properly, the NTO can significantly improve network Quality of Service (QoS)

Digitizing Sociology: Continuity and Change in the Internet Era

This article outlines and contextualizes the development of digital sociology as an introduction to this e-special issue, charting the development of the field through the pages of the journal, Sociology. In doing so, the article sketches key contours of this rich and varied terrain, accenting how technological innovation has permeated the domains of politics, culture and society. Of central concern has been the intellectual origins of ‘digital sociology’. While first coined in 2009, the article highlights a longer history, noting the continued resonance of modernity’s currents of categorization, ordering and rationality while recognizing the crucial shifts brought by digitally mediated life. The article then discusses landmark articles contributing to the development of digital sociology, beginning with interventions seeking to theorize digital society. We then turn to articles focusing on methodological questions before addressing the digital turn in selected areas of enduring sociological concern including: work and organizations; inequality; migration; activism; communities; emotions; and everyday life. The article concludes with a series of observations regarding potential futures of digital sociological analyses

Evaluating Network Analysis and Agent Based Modeling for Investigating the Stability of Commercial Air Carrier Schedules

For a number of years, the United States Federal Government has been formulating the Next Generation Air Transportation System plans for National Airspace System improvement. These improvements attempt to address air transportation holistically, but often address individual improvements in one arena such as ground or in-flight equipment. In fact, air transportation system designers have had only limited success using traditional Operations Research and parametric modeling approaches in their analyses of innovative operations. They need a systemic methodology for modeling of safety-critical infrastructure that is comprehensive, objective, and sufficiently concrete, yet simple enough to be deployed with reasonable investment. The methodology must also be amenable to quantitative analysis so issues of system safety and stability can be rigorously addressed

A Multiple Case Study Analysis of Digital Preservation Techniques across Government, Private, and Public Service Organizations

The process of record keeping has evolved through time. As our technology advances, so does our ability to manage information. We have progressed from paper-based records to new digital techniques and formats to store records. However, digital storage is not the Holy Grail answer to preservation and storage problems. Digital storage is confounded by multiple problems, also. Some of these problems are, but not limited to, lack of standardization and legal guidance, proprietary formats, and the fragility of the digital medium. This research examines several organizations that are deeply involved in digital preservation and tries to identify common practices and problems across the industry

Evidence Synthesis for Stochastic Epidemic Models.

In recent years, the role of epidemic models in informing public health policies has progressively grown. Models have become increasingly realistic and more complex, requiring the use of multiple data sources to estimate all quantities of interest. This review summarises the different types of stochastic epidemic models that use evidence synthesis and highlights current challenges

Airborne Network Optimization with Dynamic Network Update

Modern networks employ congestion and routing management algorithms that can perform routing when network routes become congested. However, these algorithms may not be suitable for modern military Mobile Ad-hoc Networks (MANETs), more specifically, airborne networks, where topologies are highly dynamic and strict Quality of Service (QoS) requirements are required for mission success. These highly dynamic networks require higher level network controllers that can adapt quickly to network changes with limited interruptions and require small amounts of network bandwidth to perform routing. This thesis advocates the use of Kalman filters to predict network congestion in airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The network controller designed and implement in this thesis will take in the current and predicted queue size values to make intelligent network optimization decisions. These decisions will enhance the overall network throughput by reducing the number of dropped packets when compared with current static network and MANET protocols