Selective extinction of marine plankton at the end of the Mesozoic era: The fossil and stable isotope record

Floral, faunal and stable isotope evidence in a continuous sequence of latest Cretaceous and earliest Tertiary shallow water marine deposits in the Mangyshlak Peninsula, USSR suggest severe environmental changes at the Cretaceous/Tertiary (K/T) boundary. Time frame is provided by nanno, micro and macrofossils as well as by magnetic stratigraphy and an iridium spike. Oxygen isotopic analyses of the bulk sediments, composed of nanno and microplankton skeletal remains, show a sharp positive spike at the K/T boundary. This shift is primarily attributed to severe cooling possibly accompanied by increased salinities of the surface mixed layer. Floral and faunal extinctions were selective, affecting approximately 90 percent of the warm water calcareous phyto and zooplankton genera in the Tethyan-Paratethyan regions. These highly diverse taxa with many endemic representatives were at the peak of their evolutionary development. Geologic evidence indicates that the terminal Cretaceous temperature decline was coeval with widespread and intense volcanic activity which reached a peak at the close of the Mesozoic Era. Increased acidity temporarily prohibited calcite nucleation of the surface dwelling warm-water plankton. Superimposed upon decreased alkalinity, severe and rapid climatic changes caused the extinction of calcareous phyto and zooplankton

Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan.

A Bayesian model averaging procedure is presented within the class of vector autoregressive (VAR) processes and applied to two empirical issues. First, stability of the Great Ratios in U.S. macro-economic time series is investigated, together with the presence and effects of permanent shocks. Measures on manifolds are employed in order to elicit uniform priors on subspaces defined by particular structural features of linear VARs. Second, the VAR model is extended to include a smooth transition function in a (monetary) equation and stochastic volatility in the disturbances. The risk of a liquidity trap in the USA, UK and Japan is evaluated, together with the expected cost of a policy adjustment of central banks. Posterior probabilities of different models are evaluated usingMarkov chainMonte Carlo techniques.

Evidence on a DSGE Business Cycle model subject to Neutral and Investment-Specific Technology Shocks using Bayesian Model Averaging

The empirical support for a DSGE type of real business cycle model with two technology shocks is evaluated using a Bayesian model averaging procedure that makes use of a finite mixture of many models within the class of vector autoregressive (VAR) processes. The linear VAR model is extended to permit equilibrium restrictions and restrictions on long-run responses to technology shocks apart from having a range of lag structures and deterministic processes. These model features are weighted as posterior probabilites and computed using MCMC and analytical methods. Uncertainty exists as to the most appropriate model for our data, with five models receiving significant support. The model set used has substantial implications for the results obtained. We do find support for a number of features implied by the real business cycle model. Business cycle volatility seems more due to investment specific technology shocks than neutral technology shocks and this result is robust to model specification. These techonolgy schocks appear to account for all stochastic trends in our system after 1984. we provide evidence on the uncertainty bands associated with these results.

Model Uncertainty and Bayesian Model Averaging in Vector Autoregressive Processes

Economic forecasts and policy decisions are often informed by empirical analysis based on econometric models. However, inference based upon a single model, when several viable models exist, limits its usefulness. Taking account of model uncertainty, a Bayesian model averaging procedure is presented which allows for unconditional inference within the class of vector autoregressive (VAR) processes. Several features of VAR process are investigated. Measures on manifolds are employed in order to elicit uniform priors on subspaces defined by particular structural features of VARs. The features considered are the number and form of the equilibrium economic relations and deterministic processes. Posterior probabilities of these features are used in a model averaging approach for forecasting and impulse response analysis. The methods are applied to investigate stability of the "Great Ratios" in U.S. consumption, investment and income, and the presence and effects of permanent shocks in these series. The results obtained indicate the feasibility of the proposed method.Posterior probability; Grassman manifold; Orthogonal group; Cointegration; Model averaging; Stochastic trend; Impulse response; Vector autoregressive model.

Improper priors with well defined Bayes Factors

While some improper priors have attractive properties, it is generally claimed that Bartlett’s paradox implies that using improper priors for the parameters in alternative models results in Bayes factors that are not well defined, thus preventing model comparison in this case. In this paper we demonstrate, using well understood principles underlying what is already common practice, that this latter result is not generally true and so expand the class of priors that may be used for computing posterior odds to two classes of improper priors: the shrink age prior; and a prior based upon a nesting argument. Using a new representation of the issue of undefined Bayes factors, we develop classes of improper priors from which well defined Bayes factors result. However, as the use of such priors is not free of problems, we include discussion on the issues with using such priors for model comparison.Improper prior; Bayes factor; marginal likelihood; shrinkage prior; measure

Adaptive Mixture of Student-t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit

This paper presents the R package AdMit which provides flexible functions to approximate a certain target distribution and to efficiently generate a sample of random draws from it, given only a kernel of the target density function. The core algorithm consists of the function AdMit which fits an adaptive mixture of Student-t distributions to the density of interest. Then, importance sampling or the independence chain Metropolis-Hastings algorithm is used to obtain quantities of interest for the target density, using the fitted mixture as the importance or candidate density. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. The relevance of the package is shown in two examples. The first aims at illustrating in detail the use of the functions provided by the package in a bivariate bimodal distribution. The second shows the relevance of the adaptive mixture procedure through the Bayesian estimation of a mixture of ARCH model fitted to foreign exchange log-returns data. The methodology is compared to standard cases of importance sampling and the Metropolis-Hastings algorithm using a naive candidate and with the Griddy-Gibbs approach.

Seeing the Divine through Windows: Online Puja and Virtual Religious Experience

“Seeing the Divine through Windows: Online Puja and Virtual Religious Experience” will attempt to use phenomenological methodology to parse the meanings and uses of Internet religion itself. Hindu cyber-darshan/puja may be the ultimate long-distance religious experience, but most often, religious experience in Hinduism includes actions and reactions that occur in real time and space. During these practices, darshan is produced for the deity and the worshipper. Any description of darshan must now deal with the complex religious experience of the intertwining sight/site and location of the form of the deity. Cyber-darshan is being performed daily at a Swaminarayan Mandir in Downey, California. I began to be a regular visitor on site, watching the proceedings being captured for posting on the Internet. The temple web site offers the possibility of myriad darshanic experiences: on the homepage, there was the link directly to “Online Darshan.” Surveys of the members showed that over half the Sampradaya utilizes the resources developed by the Swaminarayan webmasters both in California and in Vadtal, India. This article will attempt to analyze the situation in which the computer has become a legitimate open portal through which Hindu religious experience can pass back and forth. The focus of will be on the ever- flexible definitions of ritual and the crucial Hindu religious experience of darshan in the context of the 21st century technological revolution