Frequentist tests for Bayesian models

Analogues of the frequentist chi-square and F tests are proposed for testing goodness-of-fit and consistency for Bayesian models. Simple examples exhibit these tests' detection of inconsistency between consecutive experiments with identical parameters, when the first experiment provides the prior for the second. In a related analysis, a quantitative measure is derived for judging the degree of tension between two different experiments with partially overlapping parameter vectors.Comment: 8 pages, 4 figures. Section 8 rewritten. Additional references. Accepted by Astronomy & Astrophysic

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

Pricing options in a fuzzy environment

Includes abstract.Includes bibliographical references (leaves 114-116).Although Fuzzy Logic is not new, it is however only since 2004 that an axiomatic theory has been created that has all the desirable effects of Fuzzy Logic. This theory, named Credibility theory was proposed by Dr. Liu. Within this thesis we aim to utilize credibility theory to model the psychological impacts of market participants on European options. Specifically this is done by modifying the approach that was originally taken by Black and Scholes. The Hew model, which is known as the fuzzy drift parameter model, begins by replacing the deterministic drift within Brownian motion with a fuzzy parameter. This fuzzy parameter models the psychological impacts of market participants. Naturally as we are dealing in Chance theory 1 the risk neutral dynamics change from that of Black and Scholes and thus so does the price of European call options

Variable modeling of fuzzy phenomena with industrial applications

Includes abstract. Includes bibliographical references (leaves 98-100)

ASSOCIATON TESTS THAT ACCOMMODATE GENOTYPING ERRORS

High-throughput SNP arrays provide estimates of genotypes for up to one million loci, often used in genome-wide association studies. While these estimates are typically very accurate, genotyping errors do occur, which can influence in particular the most extreme test statistics and p-values. Estimates for the genotype uncertainties are also available, although typically ignored. In this manuscript, we develop a framework to incorporate these genotype uncertainties in case-control studies for any genetic model. We verify that using the assumption of a “local alternative” in the score test is very reasonable for effect sizes typically seen in SNP association studies, and show that the power of the score test is simply a function of the correlation of the genotype probabilities with the true genotypes. We demonstrate that the power to detect a true association can be substantially increased for difficult to call genotypes, resulting in improved inference in association studies

Credibility and Policy Convergence: Evidence from U.S. House Roll Call Voting Records

Traditional models of politician behavior predict complete or partial policy convergence, whereby electoral competition compels partisan politicians to choose positions more moderate than their most-preferred policies. Alternatively, if politicians cannot overcome the inability to make binding pre-commitments to policies, the expected result is complete policy divergence. By exploiting a regression discontinuity (RD) design inherent in the Congressional electoral system, this paper empirically tests the strong predictions of the complete divergence hypothesis against the alternative of partial convergence within the context of Representatives' roll call voting behavior in the U.S. House (1946-1994). The RD design implies that which party wins a district seat is quasi-randomly assigned among elections that turn out to be 'close'. We use this variation to examine if Representatives' roll call voting patterns do not respond to large exogenous changes in the probability of winning the election, the strong prediction of complete policy divergence. The evidence is more consistent with full divergence and less consistent with partial convergence, suggestive that the difficulty of establishing credible commitments to policies is an important real-world phenomenon.