29,678 research outputs found

    The PyCBC search for gravitational waves from compact binary coalescence

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    We describe the PyCBC search for gravitational waves from compact-object binary coalescences in advanced gravitational-wave detector data. The search was used in the first Advanced LIGO observing run and unambiguously identified two black hole binary mergers, GW150914 and GW151226. At its core, the PyCBC search performs a matched-filter search for binary merger signals using a bank of gravitational-wave template waveforms. We provide a complete description of the search pipeline including the steps used to mitigate the effects of noise transients in the data, identify candidate events and measure their statistical significance. The analysis is able to measure false-alarm rates as low as one per million years, required for confident detection of signals. Using data from initial LIGO's sixth science run, we show that the new analysis reduces the background noise in the search, giving a 30% increase in sensitive volume for binary neutron star systems over previous searches.Comment: 29 pages, 7 figures, accepted by Classical and Quantum Gravit

    Real-time inflation forecast densities from ensemble phillips curves

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    A popular macroeconomic forecasting strategy takes combinations across many models to hedge against model instabilities of unknown timing; see (among others) Stock andWatson (2004) and Clark and McCracken (2009). In this paper, we examine the effectiveness of recursive-weight and equal-weight combination strategies for density forecasting using a time-varying Phillips curve relationship between inflation and the output gap. The densities reflect the uncertainty across a large number of models using many statistical measures of the output gap, allowing for a single structural break of unknown timing. We use real-time data for the US, Australia, New Zealand and Norway. Our main finding is that the recursive-weight strategy performs well across the real-time data sets, consistently giving well-calibrated forecast densities. The equal-weight strategy generates poorly-calibrated forecast densities for the US and Australian samples. There is little difference between the two strategies for our New Zealand and Norwegian data. We also find that the ensemble modeling approach performs more consistently with real-time data than with revised data in all four countries

    Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts

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    This paper reviews recently proposed likelihood ratio tests of goodness-of-fit and independence of interval forecasts. It recasts them in the framework of Pearson chi-squared statistics, and extends them to density forecasts. Two further recent developments are also incorporated, namely a more informative decomposition of the goodness-of-fit statistic, and the calculation of exact P-values. Examples considered are the US Survey of Professional Forecasters density forecasts of inflation and the Bank of England fan charts. This first evaluation of the Bank forecasts finds that the fan charts fan out too quickly, and the excessive concern with the upside risks was not justified.

    Fast Two-Sample Testing with Analytic Representations of Probability Measures

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    We propose a class of nonparametric two-sample tests with a cost linear in the sample size. Two tests are given, both based on an ensemble of distances between analytic functions representing each of the distributions. The first test uses smoothed empirical characteristic functions to represent the distributions, the second uses distribution embeddings in a reproducing kernel Hilbert space. Analyticity implies that differences in the distributions may be detected almost surely at a finite number of randomly chosen locations/frequencies. The new tests are consistent against a larger class of alternatives than the previous linear-time tests based on the (non-smoothed) empirical characteristic functions, while being much faster than the current state-of-the-art quadratic-time kernel-based or energy distance-based tests. Experiments on artificial benchmarks and on challenging real-world testing problems demonstrate that our tests give a better power/time tradeoff than competing approaches, and in some cases, better outright power than even the most expensive quadratic-time tests. This performance advantage is retained even in high dimensions, and in cases where the difference in distributions is not observable with low order statistics

    Children’s improvement of a motor response during backward falls through the implementation of a safe fall program

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    The World Health Organization has warned that, in children, the second cause of death from unintentional injuries are falls. The objective of this study was to analyze the motor response of primary schoolchildren when a backwards fall occurs. These analyses occurred before and after interventions of the Safe Fall program, which aims to teach safe and protected ways of backward falling. A quasi-experimental research design was used, with a sample of 122 Spanish (Sevillian) schoolchildren in the 10–12 age bracket. The INFOSECA ad-hoc observation scale was used for data collection: this scale registers 5 essential physical reactions throughout the process of a safe and protected backwards fall. After that, a number of descriptive, correlational and contrast statistics were applied. The value used in the McNemar test to establish statistical significance was p < 0.05. Results showed that over 85% of students had developed the competence to correctly perform all five physical motions that allow for a safer backward fall. The teaching of safe and protected techniques for falling backwards in child population in Primary Education is possible through the implementation of the Safe Fall program in Physical Education classes, which can help making falls safer, diminishing the risk and severity of the injuries they cause
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