Methods for inference in large multiple-equation Markov-switching models

The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of free parameters in the transition matrix to grow as the square of the number of states but also without losing a convenient form for the posterior distribution of the transition matrix. Calculation of marginal data densities for assessing model fit is often difficult in high-dimensional models and seems particularly difficult in these models. This paper gives a detailed explanation of methods we have found to work to overcome these difficulties. It also makes suggestions for maximizing posterior density and initiating Markov chain Monte Carlo simulations that provide some robustness against the complex shape of the likelihood in these models. These difficulties and remedies are likely to be useful generally for Bayesian inference in large time-series models. The paper includes some discussion of model specification issues that apply particularly to structural vector autoregressions with a Markov-switching structure.

Triple Non-negative Matrix Factorization Technique for Sentiment Analysis and Topic Modeling

Topic modeling refers to the process of algorithmically sorting documents into categories based on some common relationship between the documents. This common relationship between the documents is considered the “topic” of the documents. Sentiment analysis refers to the process of algorithmically sorting a document into a positive or negative category depending whether this document expresses a positive or negative opinion on its respective topic. In this paper, I consider the open problem of document classification into a topic category, as well as a sentiment category. This has a direct application to the retail industry where companies may want to scour the web in order to find documents (blogs, Amazon reviews, etc.) which both speak about their product, and give an opinion on their product (positive, negative or neutral). My solution to this problem uses a Non-negative Matrix Factorization (NMF) technique in order to determine the topic classifications of a document set, and further factors the matrix in order to discover the sentiment behind this category of product

Keys to Successful Implementation and Sustainment of Managed Maintenance for Healthcare Facilities

Health care providers are faced with two critical issues in today\u27s evolving marketplace: lowering operational costs and achieving more efficient, cost-effective methods to deliver high quality patient care. The rising costs of healthcare and decreasing budgets have placed additional strain on the United States Air Force Medical Service to aggressively lower its facilities\u27 costs. With fewer funds and less personnel, the Air Force medical service is re-evaluating its current maintenance outsourcing implementation practices and reexamining how these strategies might be implemented and sustained more successfully. This research offers some of the foundational needs for designing, implementing and sustaining any type of outsourcing effort. Additionally this study highlighted some DoD specific issues to program management, focusing on some of the unique attributes associated with successfully managing and sustaining a DoD medical facility maintenance program. Content analysis was used to determine the ingredients for successful outsourcing implementation and sustainment

Indeterminacy in a Forward Looking Regime Switching Model

This paper is about the properties of Markov switching rational expectations (MSRE) models. We present a simple monetary policy model that switches between two regimes with known transition probabilities. The first regime, treated in isolation, has a unique determinate rational expectations equilibrium and the second contains a set of indeterminate sunspot equilibria. We show that the Markov switching model, which randomizes between these two regimes, may contain a continuum of indeterminate equilibria. We provide examples of stationary sunspot equilibria and bounded sunspot equilibria which exist even when the MSRE model satisfies a 'generalized Taylor principle'. Our result suggests that it may be more difficult to rule out non-fundamental equilibria in MRSE models than in the single regime case where the Taylor principle is known to guarantee local uniqueness.

Transparency, expectations, and forecasts

In 1994, the Federal Open Market Committee (FOMC) began to release statements after each meeting. This paper investigates whether the public’s views about the current path of the economy and of future policy have been affected by changes in the Federal Reserve’s communications policy as reflected in private sector’s forecasts of future economic conditions and policy moves. In particular, has the ability of private agents to predict where the economy is going improved since 1994? If so, on which dimensions has the ability to forecast improved? We find evidence that the individuals’ forecasts have been more synchronized since 1994, implying the possible effects of the FOMC’s transparency. On the other hand, we find little evidence that the common forecast errors, which are the driving force of overall forecast errors, have become smaller since 1994.

Clinical Risk and Judicial Reasoning: Eugene F. Sanger, AM, MD, 1829–1897

This biographical sketch of Eugene F. Sanger, AM, MD, corresponds to the historic text, The Classic: Report of the Committee on Suits for Malpractice, available at DOI 10.1007/s11999-008-0639-z

An Activity-Based Nanosensor for Traumatic Brain Injury.

Currently, traumatic brain injury (TBI) is detected by medical imaging; however, medical imaging requires expensive capital equipment, is time- and resource-intensive, and is poor at predicting patient prognosis. To date, direct measurement of elevated protease activity has yet to be utilized to detect TBI. In this work, we engineered an activity-based nanosensor for TBI (TBI-ABN) that responds to increased protease activity initiated after brain injury. We establish that a calcium-sensitive protease, calpain-1, is active in the injured brain hours within injury. We then optimize the molecular weight of a nanoscale polymeric carrier to infiltrate into the injured brain tissue with minimal renal filtration. A calpain-1 substrate that generates a fluorescent signal upon cleavage was attached to this nanoscale polymeric carrier to generate an engineered TBI-ABN. When applied intravenously to a mouse model of TBI, our engineered sensor is observed to locally activate in the injured brain tissue. This TBI-ABN is the first demonstration of a sensor that responds to protease activity to detect TBI

PROFITABILITY OF ESTABLISHING BASIN WILDRYE FOR WINTER GRAZING

This study examined the economic viability of establishing basin wildrye for winter grazing. Mixed integer-programming models were developed that minimized cow feed costs. Estimated basin wildrye establishment costs were $154 per acre. Break-even basin wildrye yields were approximately 2.6 and 2.3 AUMs/acre for March and May calving scenarios, respectively.Livestock Production/Industries,