A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?

Predicting historic temperatures based on tree rings, ice cores, and other natural proxies is a difficult endeavor. The relationship between proxies and temperature is weak and the number of proxies is far larger than the number of target data points. Furthermore, the data contain complex spatial and temporal dependence structures which are not easily captured with simple models. In this paper, we assess the reliability of such reconstructions and their statistical significance against various null models. We find that the proxies do not predict temperature significantly better than random series generated independently of temperature. Furthermore, various model specifications that perform similarly at predicting temperature produce extremely different historical backcasts. Finally, the proxies seem unable to forecast the high levels of and sharp run-up in temperature in the 1990s either in-sample or from contiguous holdout blocks, thus casting doubt on their ability to predict such phenomena if in fact they occurred several hundred years ago. We propose our own reconstruction of Northern Hemisphere average annual land temperature over the last millennium, assess its reliability, and compare it to those from the climate science literature. Our model provides a similar reconstruction but has much wider standard errors, reflecting the weak signal and large uncertainty encountered in this setting.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS398 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

An Improved Algorithm for Generating Database Transactions from Relational Algebra Specifications

Alloy is a lightweight modeling formalism based on relational algebra. In prior work with Fisler, Giannakopoulos, Krishnamurthi, and Yoo, we have presented a tool, Alchemy, that compiles Alloy specifications into implementations that execute against persistent databases. The foundation of Alchemy is an algorithm for rewriting relational algebra formulas into code for database transactions. In this paper we report on recent progress in improving the robustness and efficiency of this transformation

Predicting Securities Fraud Settlements and Amounts: A Hierarchical Bayesian Model of Federal Securities Class Action Lawsuits

This paper develops models that predict the incidence and amount of settlements for federal class action securities fraud litigation in the post-PLSRA period. We build hierarchical Bayesian models using data which comes principally from Risk metrics and identify several important predictors of settlement incidence (e.g., the number of different types of securities associated with a case, the company return during the class period) and settlement amount (e.g., market capitalization, measures of newsworthiness). Our models allow us to estimate how the circuit court a case is filed in as well as the industry of the plaintiff firm associate with settlement outcomes. They also allow us to accurately assess the variance of individual case outcomes revealing substantial amounts of heterogeneity in variance across cases

Predicting Securities Fraud Settlements and Amounts: A Hierarchical Bayesian Model of Federal Securities Class Action Lawsuits

This article develops models that predict the incidence and amount of settlements for federal class action securities fraud litigation in the post-PLSRA period. We build hierarchical Bayesian models using data that come principally from Riskmetrics and identify several important predictors of settlement incidence (e.g., the number of different types of securities associated with a case, the company return during the class period) and settlement amount (e.g., market capitalization, measures of newsworthiness). Our models also allow us to estimate how the circuit court a case is filed in as well as the industry of the plaintiff firm associate with settlement outcomes. Finally, they allow us to accurately assess the variance of individual case outcomes revealing substantial amounts of heterogeneity in variance across cases

Predicting Securities Fraud Settlements and Amounts: A Hierarchical Bayesian Model of Federal Securities Class Action Lawsuits

This article develops models that predict the incidence and amount of settlements for federal class action securities fraud litigation in the post-PLSRA period. We build hierarchical Bayesian models using data that come principally from Riskmetrics and identify several important predictors of settlement incidence (e.g., the number of different types of securities associated with a case, the company return during the class period) and settlement amount (e.g., market capitalization, measures of newsworthiness). Our models also allow us to estimate how the circuit court a case is filed in as well as the industry of the plaintiff firm associate with settlement outcomes. Finally, they allow us to accurately assess the variance of individual case outcomes revealing substantial amounts of heterogeneity in variance across cases

Post-Traumatic Stress Disorder and Other Mental Health Problems in the Military: Oversight Issues for Congress

This report discusses the prevalence of different psychological health concerns within the Armed Forces, current mental health screening and treatments, and DOD responses

Military Medical Care: Questions and Answers

This report answers several frequently asked questions about military health care, including: how the system is structured, a TRICARE summary, TRICARE eligibility and plan options, cost of military health care to beneficiaries, relationship of TRICARE to MEDICARE, how the Affordable Care Act affects TRICARE, long-term trends of defense health care costs, and a summary of the fund which funds TRICARE

Military Medical Care: Questions and Answers

Report that answers several frequently asked questions about military health care, including: how the system is structured, a TRICARE summary, TRICARE eligibility and plan options, cost of military health care to beneficiaries, relationship of TRICARE to MEDICARE, how the Affordable Care Act affects TRICARE, long-term trends of defense health care costs, and a summary of the fund which funds TRICARE