Constraining Isocurvature Initial Conditions with WMAP 3-year data

We present constraints on the presence of isocurvature modes from the temperature and polarization CMB spectrum data from the WMAP satellite alone, and in combination with other datasets including SDSS galaxy survey and SNLS supernovae. We find that the inclusion of polarization data allows the WMAP data alone, as well as in combination with complementary observations, to place improved limits on the contribution of CDM and neutrino density isocurvature components individually. With general correlations, the upper limits on these sub-dominant isocurvature components are reduced to ~60% of the first year WMAP results, with specific limits depending on the type of fluctuations. If multiple isocurvature components are allowed, however, we find that the data still allow a majority of the initial power to come from isocurvature modes. As well as providing general constraints we also consider their interpretation in light of specific theoretical models like the curvaton and double inflation.Comment: 8 pages, 7 figures. Revised Sec 4 and Figs 3-4 post-publication to correct an error for models with varying isocurvature spectral inde

THERMAL RADIATION FROM MAGNETIZED NEUTRON STARS: A look at the Surface of a Neutron Star.

Surface thermal emission has been detected by ROSAT from four nearby young neutron stars. Assuming black body emission, the significant pulsations of the observed light curves can be interpreted as due to large surface temperature differences produced by the effect of the crustal magnetic field on the flow of heat from the hot interior toward the cooler surface. However, the energy dependence of the modulation observed in Geminga is incompatible with blackbody emission: this effect will give us a strong constraint on models of the neutron star surface.Comment: 10 pages. tar-compressed and uuencoded postcript file. talk given at the `Jubilee Gamow Seminar', St. Petersburg, Sept. 1994

Harold Jeffreys's Theory of Probability Revisited

Published exactly seventy years ago, Jeffreys's Theory of Probability (1939) has had a unique impact on the Bayesian community and is now considered to be one of the main classics in Bayesian Statistics as well as the initiator of the objective Bayes school. In particular, its advances on the derivation of noninformative priors as well as on the scaling of Bayes factors have had a lasting impact on the field. However, the book reflects the characteristics of the time, especially in terms of mathematical rigor. In this paper we point out the fundamental aspects of this reference work, especially the thorough coverage of testing problems and the construction of both estimation and testing noninformative priors based on functional divergences. Our major aim here is to help modern readers in navigating in this difficult text and in concentrating on passages that are still relevant today.Comment: This paper commented in: [arXiv:1001.2967], [arXiv:1001.2968], [arXiv:1001.2970], [arXiv:1001.2975], [arXiv:1001.2985], [arXiv:1001.3073]. Rejoinder in [arXiv:0909.1008]. Published in at http://dx.doi.org/10.1214/09-STS284 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Bayesian approach to the follow-up of candidate gravitational wave signals

Ground-based gravitational wave laser interferometers (LIGO, GEO-600, Virgo and Tama-300) have now reached high sensitivity and duty cycle. We present a Bayesian evidence-based approach to the search for gravitational waves, in particular aimed at the followup of candidate events generated by the analysis pipeline. We introduce and demonstrate an efficient method to compute the evidence and odds ratio between different models, and illustrate this approach using the specific case of the gravitational wave signal generated during the inspiral phase of binary systems, modelled at the leading quadrupole Newtonian order, in synthetic noise. We show that the method is effective in detecting signals at the detection threshold and it is robust against (some types of) instrumental artefacts. The computational efficiency of this method makes it scalable to the analysis of all the triggers generated by the analysis pipelines to search for coalescing binaries in surveys with ground-based interferometers, and to a whole variety of signal waveforms, characterised by a larger number of parameters.Comment: 9 page

A TV-Gaussian prior for infinite-dimensional Bayesian inverse problems and its numerical implementations

Many scientific and engineering problems require to perform Bayesian inferences in function spaces, in which the unknowns are of infinite dimension. In such problems, choosing an appropriate prior distribution is an important task. In particular we consider problems where the function to infer is subject to sharp jumps which render the commonly used Gaussian measures unsuitable. On the other hand, the so-called total variation (TV) prior can only be defined in a finite dimensional setting, and does not lead to a well-defined posterior measure in function spaces. In this work we present a TV-Gaussian (TG) prior to address such problems, where the TV term is used to detect sharp jumps of the function, and the Gaussian distribution is used as a reference measure so that it results in a well-defined posterior measure in the function space. We also present an efficient Markov Chain Monte Carlo (MCMC) algorithm to draw samples from the posterior distribution of the TG prior. With numerical examples we demonstrate the performance of the TG prior and the efficiency of the proposed MCMC algorithm

Model-based estimates of the finite population mean for two-stage cluster samples with unit non-response

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74917/1/j.1467-9876.2007.00566.x.pd

Bayesian coherent analysis of in-spiral gravitational wave signals with a detector network

The present operation of the ground-based network of gravitational-wave laser interferometers in "enhanced" configuration brings the search for gravitational waves into a regime where detection is highly plausible. The development of techniques that allow us to discriminate a signal of astrophysical origin from instrumental artefacts in the interferometer data and to extract the full range of information are some of the primary goals of the current work. Here we report the details of a Bayesian approach to the problem of inference for gravitational wave observations using a network of instruments, for the computation of the Bayes factor between two hypotheses and the evaluation of the marginalised posterior density functions of the unknown model parameters. The numerical algorithm to tackle the notoriously difficult problem of the evaluation of large multi-dimensional integrals is based on a technique known as Nested Sampling, which provides an attractive alternative to more traditional Markov-chain Monte Carlo (MCMC) methods. We discuss the details of the implementation of this algorithm and its performance against a Gaussian model of the background noise, considering the specific case of the signal produced by the in-spiral of binary systems of black holes and/or neutron stars, although the method is completely general and can be applied to other classes of sources. We also demonstrate the utility of this approach by introducing a new coherence test to distinguish between the presence of a coherent signal of astrophysical origin in the data of multiple instruments and the presence of incoherent accidental artefacts, and the effects on the estimation of the source parameters as a function of the number of instruments in the network.Comment: 22 page

Habitat‐dependent occupancy and movement in a migrant songbird highlights the importance of mangroves and forested lagoons in Panama and Colombia

Climate change is predicted to impact tropical mangrove forests due to decreased rainfall, sea‐level rise, and increased seasonality of flooding. Such changes are likely to influence habitat quality for migratory songbirds occupying mangrove wetlands during the tropical dry season. Overwintering habitat quality is known to be associated with fitness in migratory songbirds, yet studies have focused primarily on territorial species. Little is known about the ecology of nonterritorial species that may display more complex movement patterns within and among habitats of differing quality. In this study, we assess within‐season survival and movement at two spatio‐temporal scales of a nonterritorial overwintering bird, the prothonotary warbler (Protonotaria citrea), that depends on mangroves and tropical lowland forests. Specifically, we (a) estimated within‐patch survival and persistence over a six‐week period using radio‐tagged birds in central Panama and (b) modeled abundance and occupancy dynamics at survey points throughout eastern Panama and northern Colombia as the dry season progressed. We found that site persistence was highest in mangroves; however, the probability of survival did not differ among habitats. The probability of warbler occupancy increased with canopy cover, and wet habitats were least likely to experience local extinction as the dry season progressed. We also found that warbler abundance is highest in forests with the tallest canopies. This study is one of the first to demonstrate habitat‐dependent occupancy and movement in a nonterritorial overwintering migrant songbird, and our findings highlight the need to conserve intact, mature mangrove, and lowland forests

Moving Beyond Noninformative Priors: Why and How to Choose Weakly Informative Priors in Bayesian Analyses

Throughout the last two decades, Bayesian statistical methods have proliferated throughout ecology and evolution. Numerous previous references established both philosophical and computational guidelines for implementing Bayesian methods. However, protocols for incorporating prior information, the defining characteristic of Bayesian philosophy, are nearly nonexistent in the ecological literature. Here, I hope to encourage the use of weakly informative priors in ecology and evolution by providing a ‘consumer\u27s guide’ to weakly informative priors. The first section outlines three reasons why ecologists should abandon noninformative priors: 1) common flat priors are not always noninformative, 2) noninformative priors provide the same result as simpler frequentist methods, and 3) noninformative priors suffer from the same high type I and type M error rates as frequentist methods. The second section provides a guide for implementing informative priors, wherein I detail convenient ‘reference’ prior distributions for common statistical models (i.e. regression, ANOVA, hierarchical models). I then use simulations to visually demonstrate how informative priors influence posterior parameter estimates. With the guidelines provided here, I hope to encourage the use of weakly informative priors for Bayesian analyses in ecology. Ecologists can and should debate the appropriate form of prior information, but should consider weakly informative priors as the new ‘default’ prior for any Bayesian model

Markov Chain Monte Carlo joint analysis of Chandra X-ray imaging spectroscopy and Sunyaev-Zeldovich Effect data

X-ray and Sunyaev-Zeldovich Effect data can be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from the Chandra Observatory, which provides both spatial and spectral information, and Sunyaev-Zeldovich Effect data were obtained from the BIMA and OVRO arrays. We introduce a Markov chain Monte Carlo procedure for the joint analysis of X-ray and Sunyaev-Zeldovich Effect data. The advantages of this method are the high computational efficiency and the ability to measure simultaneously the probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and also for derivative quantities such as the distance to the cluster. We demonstrate this technique by applying it to the Chandra X-ray data and the OVRO radio data for the galaxy cluster Abell 611. Comparisons with traditional likelihood-ratio methods reveal the robustness of the method. This method will be used in follow-up papers to determine the distances to a large sample of galaxy clusters.Comment: ApJ accepted, scheduled for ApJ 10 October 2004, v614 issue. Title changed, added more convergence diagnostic tests, Figure 7 converted to lower resolution for easier download, other minor change