Bayesian change-point analysis in linear regression model with scale mixtures of normal distributions

In this thesis, we consider Bayesian inference on the detection of variance change-point models with scale mixtures of normal (for short SMN) distributions. This class of distributions is symmetric and thick-tailed and includes as special cases: Gaussian, Student-t, contaminated normal, and slash distributions. The proposed models provide greater flexibility to analyze a lot of practical data, which often show heavy-tail and may not satisfy the normal assumption. As to the Bayesian analysis, we specify some prior distributions for the unknown parameters in the variance change-point models with the SMN distributions. Due to the complexity of the joint posterior distribution, we propose an efficient Gibbs-type with Metropolis- Hastings sampling algorithm for posterior Bayesian inference. Thereafter, following the idea of [1], we consider the problems of the single and multiple change-point detections. The performance of the proposed procedures is illustrated and analyzed by simulation studies. A real application to the closing price data of U.S. stock market has been analyzed for illustrative purposes.

ENVISIONING QUEER THROUGH DIGITAL MEDIA: DEVELOPING A COMMUNITY-BASED WORKSHOP IN MEDIA ANALYSIS FOR LGBTQIA+ YOUTH

This project consists of a proposed curriculum for a semester-long, community-based workshop for LGBTQIA+ (lesbian, gay, bisexual, trans*, queer or questioning, intersex, asexual or ally, "+" indicating other identifications that deviate from heterosexual) youth ages 16-18. The workshop focuses on an exploration of LGBTQIA+ identity and community through discussion and collaborative rhetorical analysis of visual and social media. Informed by queer theory and history, studies on youth work, and visual media studies and incorporating rhetorical criticism as well as liberatory pedagogy and community literacy practices, the participation-based design of the workshop seeks to involve participants in selection of media texts, active analytical viewership, and multimodal response. The workshop is designed to engage participants in reflection on questions of individual and collective responsibility and agency as members and allies of various communities. The goal of the workshop is to strengthen participants' abilities to analyze the complex ways in which television, film, and social media influence their own and others’ perceptions of issues surrounding queer identities. As part of the reflective process, participants are challenged to consider how they can in turn actively and collaboratively respond to and potentially help to shape these perceptions. My project report details the theoretical framework, pedagogical rationale, methods of text selection and critical analysis, and guidelines for conduct that inform and structure the workshop.

Adaptive sensing for target tracking applications

In a statistical inference scenario, the estimation of target signal or its parameters is done by processing data from informative measurements. The estimation performance can be enhanced if we choose the measurements based on some criteria that help to direct our sensing resources such that the measurements are more informative about the parameter we intend to estimate. While taking multiple measurements, the measurements can be chosen online so that more information could be extracted from the data in each measurement process. This approach fits well in Bayesian inference model often used to produce successive posterior distributions of the associated parameter. We explore the sensor array processing scenario for adaptive sensing of a target parameter. The measurement choice is described by a measurement matrix that multiplies the data vector normally associated with the array signal processing. The adaptive sensing of both static and dynamic system models is done by the online selection of proper measurement matrix over time. For the dynamic system model, the target is assumed to move with some distribution and the prior distribution at each time step is changed. The information gained through adaptive sensing of the moving target is lost due to the relative shift of the target. The adaptive sensing paradigm has many similarities with compressive sensing. We have attempted to reconcile the two approaches by modifying the observation model of adaptive sensing to match the compressive sensing model for the estimation of a sparse vector.

Governmentality in higher education : a critical analysis of the National Survey of Student Engagement (NSSE)

In this dissertation, the National Survey of Student Engagement (NSSE) serves as a nodal point through which to examine the power relations shaping the direction and practices of higher education in the twenty-first century. Theoretically, my analysis is informed by Foucault’s concept of governmentality, briefly defined as a technology of power that influences or shapes behavior from a distance. This form of governance operates through apparatuses of security, which include higher education. Foucault identified three essential characteristics of an apparatus—the market, the milieu, and the processes of normalization—through which administrative mechanisms and practices operate and govern populations. In this project, my primary focus is on the governance of faculty and administrators, as a population, at residential colleges and universities. I argue that the existing milieu of accountability is one dominated by the neoliberal assumption that all activity—including higher education—works best when governed by market forces alone, reducing higher education to a market-mediated private good. Under these conditions, what many in the academy believe is an essential purpose of higher education—to educate students broadly, to contribute knowledge for the public good, and to serve as society’s critic and social conscience (Washburn 227)—is being eroded. Although NSSE emerged as a form of resistance to commercial college rankings, it did not challenge the forces that empowered the rankings in the first place. Indeed, NSSE data are now being used to make institutions even more responsive to market forces. Furthermore, NSSE’s use has a normalizing effect that tends to homogenize classroom practices and erode the autonomy of faculty in the educational process. It also positions students as part of the system of surveillance. In the end, if aspects of higher education that are essential to maintaining a civil society are left to be defined solely in market terms, the result may be a less vibrant and, ultimately, a less just society.