Posterior propriety and admissibility of hyperpriors in normal hierarchical models

Hierarchical modeling is wonderful and here to stay, but hyperparameter priors are often chosen in a casual fashion. Unfortunately, as the number of hyperparameters grows, the effects of casual choices can multiply, leading to considerably inferior performance. As an extreme, but not uncommon, example use of the wrong hyperparameter priors can even lead to impropriety of the posterior. For exchangeable hierarchical multivariate normal models, we first determine when a standard class of hierarchical priors results in proper or improper posteriors. We next determine which elements of this class lead to admissible estimators of the mean under quadratic loss; such considerations provide one useful guideline for choice among hierarchical priors. Finally, computational issues with the resulting posterior distributions are addressed.Comment: Published at http://dx.doi.org/10.1214/009053605000000075 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations

Bayesian nonparametric regression with dependent wavelets has dual shrinkage properties: there is shrinkage through a dependent prior put on functional differences, and shrinkage through the setting of most of the wavelet coefficients to zero through Bayesian variable selection methods. The methodology can deal with unequally spaced data and is efficient because of the existence of fast moves in model space for the MCMC computation. The methodology is illustrated on the problem of modeling the oscillations of Cepheid variable stars; these are a class of pulsating variable stars with the useful property that their periods of variability are strongly correlated with their absolute luminosity. Once this relationship has been calibrated, knowledge of the period gives knowledge of the luminosity. This makes these stars useful as "standard candles" for estimating distances in the universe.Comment: Published in at http://dx.doi.org/10.1214/11-STS384 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Entropy-scaling search of massive biological data

Many datasets exhibit a well-defined structure that can be exploited to design faster search tools, but it is not always clear when such acceleration is possible. Here, we introduce a framework for similarity search based on characterizing a dataset's entropy and fractal dimension. We prove that searching scales in time with metric entropy (number of covering hyperspheres), if the fractal dimension of the dataset is low, and scales in space with the sum of metric entropy and information-theoretic entropy (randomness of the data). Using these ideas, we present accelerated versions of standard tools, with no loss in specificity and little loss in sensitivity, for use in three domains---high-throughput drug screening (Ammolite, 150x speedup), metagenomics (MICA, 3.5x speedup of DIAMOND [3,700x BLASTX]), and protein structure search (esFragBag, 10x speedup of FragBag). Our framework can be used to achieve "compressive omics," and the general theory can be readily applied to data science problems outside of biology.Comment: Including supplement: 41 pages, 6 figures, 4 tables, 1 bo

Analysis of intrapulse chirp in CO2 oscillators

Pulsed single-frequency CO2 laser oscillators are often used as transmitters for coherent lidar applications. These oscillators suffer from intrapulse chirp, or dynamic frequency shifting. If excessive, such chirp can limit the signal-to-noise ratio of the lidar (by generating excess bandwidth), or limit the velocity resolution if the lidar is of the Doppler type. This paper describes a detailed numerical model that considers all known sources of intrapulse chirp. Some typical predictions of the model are shown, and simple design rules to minimize chirp are proposed

Affective Trust and the Role of Social Norms in Constructing Faith in Others.

This dissertation introduces the concept of affective trust to complement the extant notions of particular and general trust in political science. While particular trust comes to explain how people generate localized expectations of others that vary across different contexts, general trust accounts for one’s default context-invariant expectation that others will act cooperatively. This project comes to explain trust in the intermediate case, in which our expectations vary across contexts, even though we lack individuated information regarding a specific agent. I argue that affective trust is a warm expectation that others are likely to act cooperatively, generated in light of social norms or institutional regularities. Social norms are the right kind of contextual feature to generate trust, since they construct both conditional preferences to act as well as first and higher order expectations that others can be expected to conform too, eliciting blame and reactive attitudes when this sort of expectation is upset. I build this account over four substantive chapters. In the first I use Herman Melville’s The Confidence Man to demonstrate the shortcomings of extant understandings of trust, while also indicating the need to rely on social conventions in order to construct trust. The second chapter offers a conceptual analysis, building conceptual intuitions by using a series of simple 2 by 2 games that come to identify trust squarely in situations of motivational uncertainty. The third chapter looks toward traditional political theory to claim that affective trust has political efficacy. Building on the recent literature on sentimental political theory, I claim that trust is the sort of epistemic feature that can explain political motivations. Using Smith, Machiavelli, and Hobbes I show the distinctly political character affective trust can take. Finally, in the fourth chapter I reflect on interviews I conducted with U.S. Christian Missionaries serving abroad to illustrate and demonstrate the plausibility of this theory. These individuals operate in environments where they lack information about the people to whom they reach out. I find that the identification of and with social norms facilitates their ability to trust others and is resonant with their experience of faith in God.PhDPolitical ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116683/1/zberger_1.pd

The Growing Complexity of Internet Interconnection

End-to-End (E2E) packet delivery in the Internet is achieved through a system of interconnections between heterogeneous entities called Autonomous Systems (ASes). The initial pattern of AS interconnection in the Internet was relatively simple, involving mainly ISPs with a balanced mixture of inbound and outbound traffic. Changing market conditions and industrial organization of the Internet have jointly forced interconnections and associated contracts to become significantly more diverse and complex. The diversity of interconnection contracts is significant because efficient allocation of costs and revenues across the Internet value chain impacts the profitability of the industry. Not surprisingly, the challenges of recovering the fixed and usage-sensitive costs of network transport give rise to more complex settlements mechanisms than the simple bifurcated (transit and peering) model described in many earlier analyses of Internet interconnection (see BESEN et al., 2001; GREENSTEIN, 2005; or LAFFONT et al., 2003). In the following, we provide insight into recent operational developments, explaining why interconnection in the Internet has become more complex, the nature of interconnection bargaining processes, the implications for cost/revenue allocation and hence interconnection incentives, and what this means for public policy. This paper offers an abbreviated version of the original paper (see FARATIN et al., 2007b).internet interconnection, economics, public policy, routing, peering.

COVID-19 pandemics and mental health: In times like these, we learn to live again

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