Precursors of extreme increments

We investigate precursors and predictability of extreme increments in a time series. The events we are focusing on consist in large increments within successive time steps. We are especially interested in understanding how the quality of the predictions depends on the strategy to choose precursors, on the size of the event and on the correlation strength. We study the prediction of extreme increments analytically in an AR(1) process, and numerically in wind speed recordings and long-range correlated ARMA data. We evaluate the success of predictions via receiver operator characteristics (ROC-curves). Furthermore, we observe an increase of the quality of predictions with increasing event size and with decreasing correlation in all examples. Both effects can be understood by using the likelihood ratio as a summary index for smooth ROC-curves

Variational Bayesian Inference of Line Spectra

In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid; and the coefficients are governed by a Bernoulli-Gaussian prior model turning model order selection into binary sequence detection. Unlike earlier works which retain only point estimates of the frequencies, we undertake a more complete Bayesian treatment by estimating the posterior probability density functions (pdfs) of the frequencies and computing expectations over them. Thus, we additionally capture and operate with the uncertainty of the frequency estimates. Aiming to maximize the model evidence, variational optimization provides analytic approximations of the posterior pdfs and also gives estimates of the additional parameters. We propose an accurate representation of the pdfs of the frequencies by mixtures of von Mises pdfs, which yields closed-form expectations. We define the algorithm VALSE in which the estimates of the pdfs and parameters are iteratively updated. VALSE is a gridless, convergent method, does not require parameter tuning, can easily include prior knowledge about the frequencies and provides approximate posterior pdfs based on which the uncertainty in line spectral estimation can be quantified. Simulation results show that accounting for the uncertainty of frequency estimates, rather than computing just point estimates, significantly improves the performance. The performance of VALSE is superior to that of state-of-the-art methods and closely approaches the Cram\'er-Rao bound computed for the true model order.Comment: 15 pages, 8 figures, accepted for publication in IEEE Transactions on Signal Processin

The power spectrum of galaxies in the 2dF 100k redshift survey

We compute the real-space power spectrum and the redshift-space distortions of galaxies in the 2dF 100k galaxy redshift survey using pseudo-Karhunen-Loeve eigenmodes and the stochastic bias formalism. Our results agree well with those published by the 2dFGRS team, and have the added advantage of producing easy-to-interpret uncorrelated minimum-variance measurements of the galaxy-galaxy, galaxy-velocity and velocity-velocity power spectra in 27 k-bands, with narrow and well-behaved window functions in the range 0.01h/Mpc < k < 0.8h/Mpc. We find no significant detection of baryonic wiggles, although our results are consistent with a standard flat Omega_Lambda=0.7 ``concordance'' model and previous tantalizing hints of baryonic oscillations. We measure the galaxy-matter correlation coefficient r > 0.4 and the redshift-distortion parameter beta=0.49+/-0.16 for r=1 (beta=0.47+/- 0.16 without finger-of-god compression). Since this is an apparent-magnitude limited sample, luminosity-dependent bias may cause a slight red-tilt in the power spectum. A battery of systematic error tests indicate that the survey is not only impressive in size, but also unusually clean, free of systematic errors at the level to which our tests are sensitive. Our measurements and window functions are available at http://www.hep.upenn.edu/~max/2df.html together with the survey mask, radial selection function and uniform subsample of the survey that we have constructed.Comment: Replaced to match accepted MNRAS version, with new radial/angular systematics plot and sigma8 typo corrected. High-res figures, power spectra, windows and our uniform galaxy subsample with mask at http://www.hep.upenn.edu/~max/2df.html or from [email protected]. 26 journal pages, 28 fig

Post-WMAP Assessment of Infrared Cutoff in the Primordial Spectrum from Inflation

The recent Cosmic Microwave Background (CMB) measurements indicate that there is power deficiency of the CMB anisotropies at large scales compared with the $\Lambda$CDM model. We have investigated the possibility of explaining such effects by a class of primordial power spectra which have infrared cutoffs close to the horizon scale. The primordial power spectrum recovered by direct deconvolution of the observed CMB angular spectrum indicates that the data prefers a sharp infrared cutoff with a localized excess (bump) just above the cutoff. We have been motivated to assess plausible extensions of simplest inflationary scenarios which readily accommodate similar form of infrared cutoff. We carry out a complete Bayesian analysis of the parameter space using {\it Markov Chain Monte Carlo} technique with such a class of primordial power spectra. We show that primordial power spectrum that have features such as an infrared cutoff followed by a subsequent excess in power give better fit to the observed data compared to a nearly scale-invariant power law or power spectrum with just a monotonic infrared cutoff. However, there is substantial room for improvement in the match to data and calls for exploration of other mechanisms that may lead to infrared cutoff even closer to that recovered by direct deconvolution approach.Comment: Changes to match version accepted for publication in PR

SUCCESS VERSUS DECISIVENESS: CONCEPTUAL DISCUSSION AND CASE STUDY

In this paper, we vindicate the relevance of the notion of success or satisfaction for the normative assessment of voting rules. We provide arguments in support of this view and emphasize the conceptual and analytical differences between this notion and that of decisiveness. The conclusions are illustrated in the case study provided by three different voting rules that have been proposed for the Council of Ministers of the European Union.Voting, European Union, Power indices

Bayesian model selection for dark energy using weak lensing forecasts

The next generation of weak lensing probes can place strong constraints on cosmological parameters by measuring the mass distribution and geometry of the low redshift universe. We show that a future all-sky tomographic cosmic shear survey with design properties similar to Euclid can provide the statistical accuracy required to distinguish between different dark energy models. Using a fiducial cosmological model which includes cold dark matter, baryons, massive neutrinos (hot dark matter), a running primordial spectral index and possible spatial curvature as well as dark energy perturbations, we calculate Fisher matrix forecasts for different dynamical dark energy models. Using a Bayesian evidence calculation we show how well a future weak lensing survey could do in distinguishing between a cosmological constant and dynamical dark energy.Comment: 12 pages, 4 figures, accepted for publication by MNRA

How to take the interstellar weather with you in pulsar timing analysis

Here we present a Bayesian method of including discrete measurements of dispersion measure due to the interstellar medium in the direction of a pulsar as prior information in the analysis of that pulsar. We use a simple simulation to show the efficacy of this method, where the inclusion of the additional measurements results in both a significant increase in the precision with which the timing model parameters can be obtained, and an improved upper limit on the amplitude of any red noise in the dataset. We show that this method can be applied where no multi-frequency data exists across much of the dataset, and where there is no simultaneous multi-frequency data for any given observing epoch. Including such information in the analysis of upcoming International Pulsar Timing Array (IPTA) and European Pulsar Timing Array (EPTA) data releases could therefore prove invaluable in obtaining the most constraining limits on gravitational wave signals within those datasets.Comment: 7 pages, 1 Table, 3 Figures. arXiv admin note: substantial text overlap with arXiv:1310.212

Disentangling the Determinants of Successful Demobilization and Reintegration

Since 1989, international efforts to end protracted conflicts in Africa, Latin America, and Asia have included sustained investments in the disarmament, demobilization, and reintegration (DDR) of combatants from the warring parties. Yet, while policy analysts have debated the organizational factors that contribute to a successful DDR program, little is known about the factors that account for successful DDR at the micro level. Using a new dataset of ex-combatants in Sierra Leone, this paper analyzes, for the first time, the individual level determinants of demobilization and reintegration. Conventional views about the importance of age and gender for understanding reintegration find little support in the data. Instead, we find that an individual’s prospect of gaining acceptance from family and neighbors depends largely on the abusiveness of the unit in which he or she fought. Finally, while internationally-funded programs designed to assist the demobilization and reintegration process may have had an effect at the macro-level, we find no evidence that those who participated in DDR programs had an easier time gaining acceptance from their families or communities as compared to those who did not participate.demobilization, reintegration, conflict, disarmament, Sierra Leone