arXiv subjects

David A. van Dyk

Publications and source records attributed to David A. van Dyk.

At least 37 records · Page 2Linked to original sources

arXiv2019

Multidimensional Data Driven Classification of Emission-line Galaxies

We propose a new soft clustering scheme for classifying galaxies in different activity classes using simultaneously 4 emission-line ratios; log([NII ]/Ha), log([SII]/Ha), log([OI]/Ha) and log([OIII]/Hb). We fit 20 multivariate Gaussian distributions to the 4-dimensional distribution of these lines obtained from the Sloan Digital Sky Survey (SDSS) in order to capture local structures and subsequently group the multivariate Gaussian distributions to represent the complex multi-dimensional structure of the joint distribution of galaxy spectra in the 4 dimensional line ratio space. The main advantages of this method are the use of all four optical-line ratios simultaneously and the adoption of a clustering scheme. This maximises the available information, avoids contradicting classifications, and treats each class as a distribution resulting in soft classification boundaries and providing the probability for an object to belong to each class. We also introduce linear multi-dimensional decision surfaces using support vector machines based on the classification of our soft clustering scheme. This linear multi-dimensional hard clustering technique shows high classification accuracy with respect to our soft-clustering scheme.

astro-ph.GA↗

arXiv2018

Calibration Concordance for Astronomical Instruments via Multiplicative Shrinkage

Calibration data are often obtained by observing several well-understood objects simultaneously with multiple instruments, such as satellites for measuring astronomical sources. Analyzing such data and obtaining proper concordance among the instruments is challenging when the physical source models are not well understood, when there are uncertainties in "known" physical quantities, or when data quality varies in ways that cannot be fully quantified. Furthermore, the number of model parameters increases with both the number of instruments and the number of sources. Thus, concordance of the instruments requires careful modeling of the mean signals, the intrinsic source differences, and measurement errors. In this paper, we propose a log-Normal hierarchical model and a more general log-t model that respect the multiplicative nature of the mean signals via a half-variance adjustment, yet permit imperfections in the mean modeling to be absorbed by residual variances. We present analytical solutions in the form of power shrinkage in special cases and develop reliable MCMC algorithms for general cases. We apply our method to several data sets obtained with a variety of X-ray telescopes such as Chandra. We demonstrate that our method provides helpful and practical guidance for astrophysicists when adjusting for disagreements among instruments.

stat.AP↗

arXiv2018

Incorporating Uncertainties in Atomic Data Into the Analysis of Solar and Stellar Observations: A Case Study in Fe XIII

Information about the physical properties of astrophysical objects cannot be measured directly but is inferred by interpreting spectroscopic observations in the context of atomic physics calculations. Ratios of emission lines, for example, can be used to infer the electron density of the emitting plasma. Similarly, the relative intensities of emission lines formed over a wide range of temperatures yield information on the temperature structure. A critical component of this analysis is understanding how uncertainties in the underlying atomic physics propagates to the uncertainties in the inferred plasma parameters. At present, however, atomic physics databases do not include uncertainties on the atomic parameters and there is no established methodology for using them even if they did. In this paper we develop simple models for the uncertainties in the collision strengths and decay rates for Fe XIII and apply them to the interpretation of density sensitive lines observed with the EUV Imagining spectrometer (EIS) on Hinode. We incorporate these uncertainties in a Bayesian framework. We consider both a pragmatic Bayesian method where the atomic physics information is unaffected by the observed data, and a fully Bayesian method where the data can be used to probe the physics. The former generally increases the uncertainty in the inferred density by about a factor of 5 compared with models that incorporate only statistical uncertainties. The latter reduces the uncertainties on the inferred densities, but identifies areas of possible systematic problems with either the atomic physics or the observed intensities.

astro-ph.SR↗

arXiv2018

Bayesian Hierarchical Modelling of Initial-Final Mass Relations Across Star Clusters

The initial-final mass relation (IFMR) of white dwarfs (WDs) plays an important role in stellar evolution. To derive precise estimates of IFMRs and explore how they may vary among star clusters, we propose a Bayesian hierarchical model that pools photo- metric data from multiple star clusters. After performing a simulation study to show the benefits of the Bayesian hierarchical model, we apply this model to five star clus- ters: the Hyades, M67, NGC 188, NGC 2168, and NGC 2477, leading to reasonable and consistent estimates of IFMRs for these clusters. We illustrate how a cluster-specific analysis of NGC 188 using its own photometric data can produce an unreasonable IFMR since its WDs have a narrow range of zero-age main sequence (ZAMS) masses. However, the Bayesian hierarchical model corrects the cluster-specific analysis by bor- rowing strength from other clusters, thus generating more reliable estimates of IFMR parameters. The data analysis presents the benefits of Bayesian hierarchical modelling over conventional cluster-specific methods, which motivates us to elaborate the pow- erful statistical techniques in this article.

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arXiv2018

A Hierarchical Model for the Ages of Galactic Halo White Dwarfs

In astrophysics, we often aim to estimate one or more parameters for each member object in a population and study the distribution of the fitted parameters across the population. In this paper, we develop novel methods that allow us to take advantage of existing software designed for such case-by-case analyses to simultaneously fit parameters of both the individual objects and the parameters that quantify their distribution across the population. Our methods are based on Bayesian hierarchical modelling which is known to produce parameter estimators for the individual objects that are on average closer to their true values than estimators based on case-by-case analyses. We verify this in the context of estimating ages of Galactic halo white dwarfs (WDs) via a series of simulation studies. Finally, we deploy our new techniques on optical and near-infrared photometry of ten candidate halo WDs to obtain estimates of their ages along with an estimate of the mean age of Galactic halo WDs of [11.25, 12.96] Gyr. Although this sample is small, our technique lays the ground work for large-scale studies using data from the Gaia mission.

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arXiv2017

A Repelling-Attracting Metropolis Algorithm for Multimodality

Although the Metropolis algorithm is simple to implement, it often has difficulties exploring multimodal distributions. We propose the repelling-attracting Metropolis (RAM) algorithm that maintains the simple-to-implement nature of the Metropolis algorithm, but is more likely to jump between modes. The RAM algorithm is a Metropolis-Hastings algorithm with a proposal that consists of a downhill move in density that aims to make local modes repelling, followed by an uphill move in density that aims to make local modes attracting. The downhill move is achieved via a reciprocal Metropolis ratio so that the algorithm prefers downward movement. The uphill move does the opposite using the standard Metropolis ratio which prefers upward movement. This down-up movement in density increases the probability of a proposed move to a different mode. Because the acceptance probability of the proposal involves a ratio of intractable integrals, we introduce an auxiliary variable which creates a term in the acceptance probability that cancels with the intractable ratio. Using several examples, we demonstrate the potential for the RAM algorithm to explore a multimodal distribution more efficiently than a Metropolis algorithm and with less tuning than is commonly required by tempering-based methods.

stat.ME↗

arXiv2017

Bayesian Estimates of Astronomical Time Delays between Gravitationally Lensed Stochastic Light Curves

The gravitational field of a galaxy can act as a lens and deflect the light emitted by a more distant object such as a quasar. Strong gravitational lensing causes multiple images of the same quasar to appear in the sky. Since the light in each gravitationally lensed image traverses a different path length from the quasar to the Earth, fluctuations in the source brightness are observed in the several images at different times. The time delay between these fluctuations can be used to constrain cosmological parameters and can be inferred from the time series of brightness data or light curves of each image. To estimate the time delay, we construct a model based on a state-space representation for irregularly observed time series generated by a latent continuous-time Ornstein-Uhlenbeck process. We account for microlensing, an additional source of independent long-term extrinsic variability, via a polynomial regression. Our Bayesian strategy adopts a Metropolis-Hastings within Gibbs sampler. We improve the sampler by using an ancillarity-sufficiency interweaving strategy and adaptive Markov chain Monte Carlo. We introduce a profile likelihood of the time delay as an approximation of its marginal posterior distribution. The Bayesian and profile likelihood approaches complement each other, producing almost identical results; the Bayesian method is more principled but the profile likelihood is simpler to implement. We demonstrate our estimation strategy using simulated data of doubly- and quadruply-lensed quasars, and observed data from quasars Q0957+561 and J1029+2623.

astro-ph.IM↗

arXiv2016

On methods for correcting for the look-elsewhere effect in searches for new physics

The search for new significant peaks over a energy spectrum often involves a statistical multiple hypothesis testing problem. Separate tests of hypothesis are conducted at different locations producing an ensemble of local p-values, the smallest of which is reported as evidence for the new resonance. Unfortunately, controlling the false detection rate (type I error rate) of such procedures may lead to excessively stringent acceptance criteria. In the recent physics literature, two promising statistical tools have been proposed to overcome these limitations. In 2005, a method to "find needles in haystacks" was introduced by Pilla et al. [1], and a second method was later proposed by Gross and Vitells [2] in the context of the "look elsewhere effect" and trial factors. We show that, for relatively small sample sizes, the former leads to an artificial inflation of statistical power that stems from an increase in the false detection rate, whereas the two methods exhibit similar performance for large sample sizes. We apply the methods to realistic simulations of the Fermi Large Area Telescope data, in particular the search for dark matter annihilation lines. Further, we discuss the counter-intutive scenario where the look-elsewhere corrections are more conservative than much more computationally efficient corrections for multiple hypothesis testing. Finally, we provide general guidelines for navigating the tradeoffs between statistical and computational efficiency when selecting a statistical procedure for signal detection.

physics.data-an↗

arXiv2016

A Bayesian Analysis of the Ages of Four Open Clusters

In this paper we apply a Bayesian technique to determine the best fit of stellar evolution models to find the main sequence turn off age and other cluster parameters of four intermediate-age open clusters: NGC 2360, NGC 2477, NGC 2660, and NGC 3960. Our algorithm utilizes a Markov chain Monte Carlo technique to fit these various parameters, objectively finding the best-fit isochrone for each cluster. The result is a high-precision isochrone fit. We compare these results with the those of traditional "by-eye" isochrone fitting methods. By applying this Bayesian technique to NGC 2360, NGC 2477, NGC 2660, and NGC 3960, we determine the ages of these clusters to be 1.35 +/- 0.05, 1.02 +/- 0.02, 1.64 +/- 0.04, and 0.860 +/- 0.04 Gyr, respectively. The results of this paper continue our effort to determine cluster ages to higher precision than that offered by these traditional methods of isochrone fitting.

astro-ph.SR↗

arXiv2016

Detecting Relativistic X-ray Jets in High-Redshift Quasars

We analyze Chandra X-ray images of a sample of 11 quasars that are known to contain kiloparsec scale radio jets. The sample consists of five high-redshift (z >= 3.6) flat-spectrum radio quasars, and six intermediate redshift (2.1 < z < 2.9) quasars. The dataset includes four sources with integrated steep radio spectra and seven with flat radio spectra. A total of 25 radio jet features are present in this sample. We apply a Bayesian multi-scale image reconstruction method to detect and measure the X-ray emission from the jets. We compute deviations from a baseline model that does not include the jet, and compare observed X-ray images with those computed with simulated images where no jet features exist. This allows us to compute p-value upper bounds on the significance that an X- ray jet is detected in a pre-determined region of interest. We detected 12 of the features unambiguously, and an additional 6 marginally. We also find residual emission in the cores of 3 quasars and in the background of 1 quasar that suggest the existence of unresolved X-ray jets. The dependence of the X-ray to radio luminosity ratio on redshift is a potential diagnostic of the emission mechanism, since the inverse Compton scattering of cosmic microwave background photons (IC/CMB) is thought to be redshift dependent, whereas in synchrotron models no clear redshift dependence is expected. We find that the high-redshift jets have X-ray to radio flux ratios that are marginally inconsistent with those from lower redshifts, suggesting that either the X-ray emissions is due to the IC/CMB rather than the synchrotron process, or that high redshift jets are qualitatively different.

astro-ph.HE↗

arXiv2016

Standardizing Type Ia supernovae using Near Infrared rebrightening time

Accurate standardisation of Type Ia supernovae (SNIa) is instrumental to the usage of SNIa as distance indicators. We analyse a homogeneous sample of 22 low-z SNIa, observed by the Carnegie Supernova Project (CSP) in the optical and near infra-red (NIR). We study the time of the second peak in the NIR band due to re-brightening, t2, as an alternative standardisation parameter of SNIa peak brightness. We use BAHAMAS, a Bayesian hierarchical model for SNIa cosmology, to determine the residual scatter in the Hubble diagram. We find that in the absence of a colour correction, t2 is a better standardisation parameter compared to stretch: t2 has a 1 sigma posterior interval for the Hubble residual scatter of [0.250, 0.257] , compared to [0.280, 0.287] when stretch (x1) alone is used. We demonstrate that when employed together with a colour correction, t2 and stretch lead to similar residual scatter. Using colour, stretch and t2 jointly as standardisation parameters does not result in any further reduction in scatter, suggesting that t2 carries redundant information with respect to stretch and colour. With a much larger SNIa NIR sample at higher redshift in the future, t2 could be a useful quantity to perform robustness checks of the standardisation procedure.

astro-ph.CO↗

arXiv2016

The Power of Principled Bayesian Methods in the Study of Stellar Evolution

It takes years of effort employing the best telescopes and instruments to obtain high-quality stellar photometry, astrometry, and spectroscopy. Stellar evolution models contain the experience of lifetimes of theoretical calculations and testing. Yet most astronomers fit these valuable models to these precious datasets by eye. We show that a principled Bayesian approach to fitting models to stellar data yields substantially more information over a range of stellar astrophysics. We highlight advances in determining the ages of star clusters, mass ratios of binary stars, limitations in the accuracy of stellar models, post-main-sequence mass loss, and the ages of individual white dwarfs. We also outline a number of unsolved problems that would benefit from principled Bayesian analyses.

astro-ph.SR↗

arXiv2016

A method for comparing non-nested models with application to astrophysical searches for new physics

Searches for unknown physics and decisions between competing astrophysical models to explain data both rely on statistical hypothesis testing. The usual approach in searches for new physical phenomena is based on the statistical Likelihood Ratio Test (LRT) and its asymptotic properties. In the common situation, when neither of the two models under comparison is a special case of the other i.e., when the hypotheses are non-nested, this test is not applicable. In astrophysics, this problem occurs when two models that reside in different parameter spaces are to be compared. An important example is the recently reported excess emission in astrophysical $γ$-rays and the question whether its origin is known astrophysics or dark matter. We develop and study a new, simple, generally applicable, frequentist method and validate its statistical properties using a suite of simulations studies. We exemplify it on realistic simulated data of the Fermi-LAT $γ$-ray satellite, where non-nested hypotheses testing appears in the search for particle dark matter.

physics.data-an↗

arXiv2015

Detecting Abrupt Changes in the Spectra of High-Energy Astrophysical Sources

Variable-intensity astronomical sources are the result of complex and often extreme physical processes. Abrupt changes in source intensity are typically accompanied by equally sudden spectral shifts, i.e., sudden changes in the wavelength distribution of the emission. This article develops a method for modeling photon counts collected from observation of such sources. We embed change points into a marked Poisson process, where photon wavelengths are regarded as marks and both the Poisson intensity parameter and the distribution of the marks are allowed to change. To the best of our knowledge this is the first effort to embed change points into a marked Poisson process. Between the change points, the spectrum is modeled non-parametrically using a mixture of a smooth radial basis expansion and a number of local deviations from the smooth term representing spectral emission lines. Because the model is over parameterized we employ an $\ell_1$ penalty. The tuning parameter in the penalty and the number of change points are determined via the minimum description length principle. Our method is validated via a series of simulation studies and its practical utility is illustrated in the analysis of the ultra-fast rotating yellow giant star known as FK Com.

stat.AP↗

arXiv2015

Detecting Unspecified Structure in Low-Count Images

Unexpected structure in images of astronomical sources often presents itself upon visual inspection of the image, but such apparent structure may either correspond to true features in the source or be due to noise in the data. This paper presents a method for testing whether inferred structure in an image with Poisson noise represents a significant departure from a baseline (null) model of the image. To infer image structure, we conduct a Bayesian analysis of a full model that uses a multiscale component to allow flexible departures from the posited null model. As a test statistic, we use a tail probability of the posterior distribution under the full model. This choice of test statistic allows us to estimate a computationally efficient upper bound on a p-value that enables us to draw strong conclusions even when there are limited computational resources that can be devoted to simulations under the null model. We demonstrate the statistical performance of our method on simulated images. Applying our method to an X-ray image of the quasar 0730+257, we find significant evidence against the null model of a single point source and uniform background, lending support to the claim of an X-ray jet.

astro-ph.IM↗

arXiv2015

Disentangling Overlapping Astronomical Sources using Spatial and Spectral Information

We present a powerful new algorithm that combines both spatial information (event locations and the point spread function) and spectral information (photon energies) to separate photons from overlapping sources. We use Bayesian statistical methods to simultaneously infer the number of overlapping sources, to probabilistically separate the photons among the sources, and to fit the parameters describing the individual sources. Using the Bayesian joint posterior distribution, we are able to coherently quantify the uncertainties associated with all these parameters. The advantages of combining spatial and spectral information are demonstrated through a simulation study. The utility of the approach is then illustrated by analysis of observations of FK Aqr and FL Aqr with the XMM-Newton Observatory and the central region of the Orion Nebula Cluster with the Chandra X-ray Observatory.

astro-ph.IM↗

arXiv2015

A Corrected and More Efficient Suite of MCMC Samplers for the Multinomal Probit Model

The multinomial probit (MNP) model is a useful tool for describing discrete-choice data and there are a variety of methods for fitting the model. Among them, the algorithms provided by Imai and van Dyk (2005a), based on Marginal Data Augmentation, are widely used, because they are efficient in terms of convergence and allow the possibly improper prior distribution to be specified directly on identifiable parameters. Burgette and Nordheim (2012) modify a model and algorithm of Imai and van Dyk (2005a) to avoid an arbitrary choice that is often made to establish identifiability. There is an error in the algorithms of Imai and van Dyk (2005a), however, which affects both their algorithms and that of Burgette and Nordheim (2012). This error can alter the stationary distribution and the resulting fitted parameters as well as the efficiency of these algorithms. We propose a correction and use both a simulation study and a real-data analysis to illustrate the difference between the original and corrected algorithms, both in terms of their estimated posterior distributions and their convergence properties. In some cases, the effect on the stationary distribution can be substantial.

stat.CO↗

arXiv2014

Metropolis-Hastings within Partially Collapsed Gibbs Samplers

The Partially Collapsed Gibbs (PCG) sampler offers a new strategy for improving the convergence of a Gibbs sampler. PCG achieves faster convergence by reducing the conditioning in some of the draws of its parent Gibbs sampler. Although this can significantly improve convergence, care must be taken to ensure that the stationary distribution is preserved. The conditional distributions sampled in a PCG sampler may be incompatible and permuting their order may upset the stationary distribution of the chain. Extra care must be taken when Metropolis-Hastings (MH) updates are used in some or all of the updates. Reducing the conditioning in an MH within Gibbs sampler can change the stationary distribution, even when the PCG sampler would work perfectly if MH were not used. In fact, a number of samplers of this sort that have been advocated in the literature do not actually have the target stationary distributions. In this article, we illustrate the challenges that may arise when using MH within a PCG sampler and develop a general strategy for using such updates while maintaining the desired stationary distribution. Theoretical arguments provide guidance when choosing between different MH within PCG sampling schemes. Finally we illustrate the MH within PCG sampler and its computational advantage using several examples from our applied work.

stat.CO↗