Bayesian analysis of elapsed times in continuous‐time Markov chains

The authors consider Bayesian analysis for continuous‐time Markov chain models based on a conditional reference prior. For such models, inference of the elapsed time between chain observations depends heavily on the rate of decay of the prior as the elapsed time increases. Moreover, improper priors on the elapsed time may lead to improper posterior distributions. In addition, an infinitesimal rate matrix also characterizes this class of models. Experts often have good prior knowledge about the parameters of this matrix. The authors show that the use of a proper prior for the rate matrix parameters together with the conditional reference prior for the elapsed time yields a proper posterior distribution. The authors also demonstrate that, when compared to analyses based on priors previously proposed in the literature, a Bayesian analysis on the elapsed time based on the conditional reference prior possesses better frequentist properties. The type of prior thus represents a better default prior choice for estimation software.     

How far does the gender gap extend?: Decision making on state Supreme Courts in Fourth Amendment Cases, 1980–2000

The importance of women on the bench and the influence of gender on judicial decision making has garnered much scholarly attention. We examine the voting behavior of male and female justices in 718 Fourth Amendment search and seizure votes cast on state Supreme Courts between 1980 and 2000. We find that women justices, controlling for institutional, political, and legal constraints, are more likely to rule in favor of the criminal defendant than their male brethren in cases decided after 1991 but not before. We also find women justices serving with female colleagues are more inclined to render liberal votes. We conclude the influence of gender may be evident in a wider variety of cases than those dealing with women's lives but that this influence is dependent upon the existence of a critical mass of women on the state court benches.     

BATHTUB-TYPE CURVES IN RELIABILITY AND BEYOND

Finding optimal, or at least good, maintenance and repair policies is crucial in reliability engineering. Likewise, describing life phases of human mortality is important when determining social policy or insurance premiums. In these tasks, one searches for distributions to fit data and then makes inferences about the population(s). In the present paper, we focus on bathtub‐type distributions and provide a view of certain problems, methods and solutions, and a few challenges, that can be encountered in reliability engineering, survival analysis, demography and actuarial science.     

Stochastic Modelling of Times to Temperature for Furnaces Supplying Titanium Blooms to a Rolling Mill at TIMET

In conjunction with TIMET at Waunarlwydd (Swansea, UK) a model has been developed that will optimise the scheduling of various blooms to their eight furnaces so as to minimise the time taken to roll these blooms into the finished mill products. This production scheduling model requires reliable data on times taken for the various furnaces that heat the slabs and blooms to reach the temperatures required for rolling. These times to temperature are stochastic in nature and this paper identifies the distributional form for these times using the generalised F distribution as a modelling framework. The times to temperature were found to be similarly distributed over all furnaces. The identified distributional forms were incorporated into the scheduling model to optimise a particular campaign that was run at TIMET Swansea. Amongst other conclusion it was found that, compared to the actual campaign, the model produced a schedule that reduced the makespan by some 35%.     

Imagined Memories

Most discussions of popular music on the Internet focus on the utopian potential of new file-sharing technologies, yet applications that reproduce existing inequalities also deserve attention. Webcasting is the streaming (transmission) of digital video to multiple recipients in cyberspace. Paul McCartney's Webcast from the Cavern was a landmark case. It was a digital package staged for reproduction, and yet it felt live; in this article I explore why and offer a two-part explanation. The first part is that "live'-ness is based on an increasingly false opposition to recording, but, because that opposition still remains, Little Big Gig could seem live by adopting some trappings associated with it. The second part is that Internet use is mediated by daily life and computer users brought their own desire to the Webcast, in particular desires to see a Beatle play in the Cavern. Webcasting is an unanticipated use of the Internet that is being used to support corporate interests. With its widespread publicity, Little Big Gig helped naturalize that process.     

Innovation,accountability, and independence at three private foundations funding higher education civic engagement, 1995 to 2005

This case study looks at changes in private foundation funding for higher education civic engagement from 1995 to 2005. The focus is three large, established foundations that were U.S. national leaders in supporting this activity during these years: Carnegie, Pew, and Kellogg. Data sources include (1) in‐depth conversations with four strategically placed foundation insiders and six nationally recognized campus leaders and (2) scans of Web sites of the three foundations that document the change in funding priorities over time, plus Web sites of the main campus initiatives supported and national campus civic engagement organizations such as Campus Compact. Research findings con‐ firm and specify other studies that suggest that foundations shift their funding priorities according to their perceived role as innovators, pressures to be accountable and show clear results, and their independence as private organizations. The article concludes by raising questions about private foundations generally in relation to issues of innovativeness, accountability, and independence.     

A spatiotemporal auto-regressive moving average model for solar radiation

Summary.  To investigate the variability in energy output from a network of photovoltaic cells, solar radiation was recorded at 10 sites every 10 min in the Pentland Hills to the south of Edinburgh. We identify spatiotemporal auto-regressive moving average models as the most appropriate to address this problem. Although previously considered computationally prohibitive to work with, we show that by approximating using toroidal space and fitting by matching auto-correlations, calculations can be substantially reduced. We find that a first-order spatiotemporal auto-regressive (STAR(1)) process with a first-order neighbourhood structure and a Matern noise process provide an adequate fit to the data, and we demonstrate its use in simulating realizations of energy output.