This study addresses seasonal predictability of South American rainfall during ENSO. The skill of empirical and coupled multi-model predictions is assessed and compared. The empirical model uses the previous season AugustSeptember-October Pacific and Atlantic sea surface temperatures as predictors for December-January-February rainfall. Coupled multi-model 1-month lead December-JanuaryFebruary ...

We present a source and lens reconstruction for the optical Einstein ring gravitational lens system RXS J1131-1231. We resolve detail in the source, which is the host galaxy of a z = 0.658 quasar, down to a resolution of 0.045 arc seconds (this is the size of the smallest conclusively resolved structures, rather than the pixel scale), using a Bayesian technique with a realistic model for the pr...

An image is never noise free. Visual inspection of a part from its image is therefore aaected by image errors. Understanding how image errors aaect measurement precision is therefore critical for accurate inspection. Existing visual inspection methods either setup a highly controlled environment to minimize image errors or simply ignore image errors. They therefore suuer from limited accuracy a...

The revelation principle is a fundamental theorem in many economics fields. In this paper, we construct a simple labor model to show that a social choice function which can be implemented costly in Bayesian Nash equilibrium may not be truthfully implementable. The key point is the strategy cost condition given in Section 4: In the direct mechanism, each agent only reports a type and will not pa...

Best-worst scaling (BWS), also known as maximum-difference scaling, is a multiattribute approach to measuring preferences. BWS aims at the analysis of preferences regarding a set of attributes, their levels or alternatives. It is a stated-preference method based on the assumption that respondents are capable of making judgments regarding the best and the worst (or the most and least important, ...

The lack of specific research on the sequence of events that determine plant growth from meristem until wood formation represents a gap in the knowledge of growth dynamics in woody species. In this work, we surveyed published studies concerning cambial activity of Brazilian native species aiming at allowing the comparison of applied methods and obtained results. The annual cambial seasonality w...

In this paper, I describe an experimental study on the efficacy of concept-based instruction in developing information retrieval skills in undergraduates. The subjects were 254 first-year undergraduates at the University of Canberra, Australia. The study followed the experimental design of a pre-test/post-test control group. The experimental group was taught information retrieval from electroni...

The problem of forecasting conditional probabilities of the next event given the past is considered in a general probabilistic setting. Given an arbitrary (large, uncountable) set C of predictors, we would like to construct a single predictor that performs asymptotically as well as the best predictor in C, on any data. Here we show that there are sets C for which such predictors exist, but none...

The use of Bayesian methods for data analysis is creating a revolution in fields ranging from genetics to marketing. Yet, results of our literature review, including more than 10,000 articles published in 15 journals from January 2001 and December 2010, indicate that Bayesian approaches are essentially absent from the organizational sciences. Our article introduces organizational science resear...

A common problem arising in new particle search experiments is to determine upper limits on a signal cross section, combining more than one channel (for example e and μ) and incorporating the effects of systematic errors, which may or may not be correlated across channels. This note describes a Bayesian procedure for performing such a calculation.