Digitizing Darwin's Library

This project which aims to reconstruct, digitally, Charles Darwin's working library as it stood at the end of his life's journey, will open up and make accessible to students of the humanities and the sciences whole new dimensions of Darwin's thinking. Over 700 of Darwin's most heavily annotated books are held at Cambridge University Library. The abundant hand-written notes on these books were painstakingly transcribed in the late 1980s. Now, thanks to high-resolution digital imagery, and an international partnership of Cambridge, the Natural History Museum in London, the Biodiversity Heritage Library-a consortium of natural history libraries, and the Darwin Digital Library of Evolution-an online scholarly edition of Darwin's manuscripts based at the American Museum of Natural History, Darwin's transcribed marginalia will be digitally married with scanned books from his own library and with scanned surrogate volumes of the exact editions Darwin owned from the partnership's libraries

Efficient Bayesian inference for multivariate factor stochastic volatility models with leverage

This paper discusses the efficient Bayesian estimation of a multivariate factor stochastic volatility (Factor MSV) model with leverage. We propose a novel approach to construct the sampling schemes that converges to the posterior distribution of the latent volatilities and the parameters of interest of the Factor MSV model based on recent advances in Particle Markov chain Monte Carlo (PMCMC). As opposed to the approach of Chib et al. (2006} and Omori et al. (2007}, our approach does not require approximating the joint distribution of outcome and volatility innovations by a mixture of bivariate normal distributions. To sample the free elements of the loading matrix we employ the interweaving method used in Kastner et al. (2017} in the Particle Metropolis within Gibbs (PMwG) step. The proposed method is illustrated empirically using a simulated dataset and a sample of daily US stock returns.Comment: 4 figures and 9 table

On Scalable Particle Markov Chain Monte Carlo

Particle Markov Chain Monte Carlo (PMCMC) is a general approach to carry out Bayesian inference in non-linear and non-Gaussian state space models. Our article shows how to scale up PMCMC in terms of the number of observations and parameters by expressing the target density of the PMCMC in terms of the basic uniform or standard normal random numbers, instead of the particles, used in the sequential Monte Carlo algorithm. Parameters that can be drawn efficiently conditional on the particles are generated by particle Gibbs. All the other parameters are drawn by conditioning on the basic uniform or standard normal random variables; e.g. parameters that are highly correlated with the states, or parameters whose generation is expensive when conditioning on the states. The performance of this hybrid sampler is investigated empirically by applying it to univariate and multivariate stochastic volatility models having both a large number of parameters and a large number of latent states and shows that it is much more efficient than competing PMCMC methods. We also show that the proposed hybrid sampler is ergodic

F as in Fat: How Obesity Threatens America's Future 2011

Outlines 2008-10 national and state obesity rates, health indicators, and policies to address the epidemic; regional, economic, and social barriers to healthy choices; impact of the 2010 healthcare reform and Let's Move initiative; and recommendations

Proper Accounting is Vital for Sustainable Business Growth

This study explains the role of accounting in business growth. In addition, this study clarifies how accounting offers support for business process. This paper demonstrates the types of services that perform by accounting. The research indicates how accounting information can be used in order to meet the needs of a business, make right decisions, and improve the company’s profitability. This article also examines why business organization often needs a way to keep score when conducting business operations. How accounting usually fits this need because it allows to company to create financial reports that enable business owners and managers to review the efficiency of operations. The conclusion of this study shows the importance of using accounting as a sophisticated financial management system for business organization's performance, growth, and expansion

Superconducting ground state of the two-dimensional Hubbard model: a variational study

A trial wave function is proposed for studying the instability of the two-dimensional Hubbard model with respect to d-wave superconductivity. Double occupancy is reduced in a similar way as in previous variational studies, but in addition our wave function both enhances the delocalization of holes and induces a kinetic exchange between the electron spins. These refinements lead to a large energy gain, while the pairing appears to be weakly affected by the additional term in the variational wave function.Comment: 2 pages, 1 figure, Proceedings of the M2S-HTSC-VII

Mixed Marginal Copula Modeling

This article extends the literature on copulas with discrete or continuous marginals to the case where some of the marginals are a mixture of discrete and continuous components. We do so by carefully defining the likelihood as the density of the observations with respect to a mixed measure. The treatment is quite general, although we focus focus on mixtures of Gaussian and Archimedean copulas. The inference is Bayesian with the estimation carried out by Markov chain Monte Carlo. We illustrate the methodology and algorithms by applying them to estimate a multivariate income dynamics model.Comment: 46 pages, 8 tables and 4 figure