Closed-form tidal approximants for binary neutron star gravitational waveforms constructed from high-resolution numerical relativity simulations

We construct closed-form gravitational waveforms (GWs) with tidal effects for the coalescence and merger of binary neutron stars. The method relies on a new set of eccentricity-reduced and high-resolution numerical relativity (NR) simulations and is composed of three steps. First, tidal contributions to the GW phase are extracted from the time-domain NR data. Second, those contributions are employed to fix high-order coefficients in an effective and resummed post-Newtonian expression. Third, frequency-domain tidal approximants are built using the stationary phase approximation. Our tidal approximants are valid from the low frequencies to the strong-field regime and up to merger. They can be analytically added to any binary black hole GW model to obtain a binary neutron star waveform, either in the time or in the frequency domain. This work provides simple, flexible, and accurate models ready to be used in both searches and parameter estimation of binary neutron star events

Salvage the treasure of geographic information in Farm census data

In Germany, since several decades the RAUMIS modelling system is applied for policy impact assessments to measure the impact of agriculture on the environment. A disaggregation at the municipality level with more than 9.600 administrative units, instead of currently used 316 counties, would tremendously improve the environmental impact analysis. Two sets of data are used for this purpose. The first are geo-referenced data, that are, however, incomplete with respect its coverage of production activities in agriculture. The second set is the micro census statistic itself, that has a full coverage, but data protection rules (DPR) prohibit its straightforward use. The paper show how this bottleneck can be passed to obtain a reliable modelling data set at municipality level with a complete coverage of the agricultural sector in Germany. We successfully applied a Bayesian estimator, that uses prior information derived a cluster analysis based on the micro census and GIS information. Our test statistics of the estimation, calculated by the statistical office, comparing our estimates and the real protected data, reveals that the proposed approach adequately estimates most activities and can be used to fed the municipality layer in the RAUMIS modelling system for an extended policy analysis.Highest Posterior Density estimator (HPD), RAUMIS, Down scaling, Research Methods/ Statistical Methods, C11, C61, C81, Q15,

BAO Extractor: bias and redshift space effects

We study a new procedure to measure the sound horizon scale via Baryonic Acoustic Oscillations (BAO). Instead of fitting the measured power spectrum (PS) to a theoretical model containing the cosmological informations and all the nonlinear effects, we define a procedure to project out (or to "extract") the oscillating component from a given nonlinear PS. We show that the BAO scale extracted in this way is extremely robust and, moreover, can be reproduced by simple theoretical models at any redshift. By using N-body simulations, we discuss the effect of the nonlinear evolution of the matter field, of redshift space distortions and of scale-dependent halo bias, showing that all these effects can be reproduced with sub-percent accuracy. We give a one-parameter theoretical model based on a simple (IR) modification of 1-loop perturbation theory, which reproduces the BAO scale from measurements of halo clustering in redshift space at better than $0.1\%$ level and does not need any external UV input, such as coefficients measured from N-body simulations.Comment: Published version. 32 pages, 15 figure

The Robust Estimation of Monthly Prices of Goods Traded by the European Union

The general problem addressed in this document is the estimation of “fair” import prices from international trade data. The work is in support to the determination of the customs value at the moment of the customs formalities, to establish how much duty the importer must pay, and the post-clearance checks of individual transactions. The proposed approach can be naturally extended to the analysis of export flows and used for other purposes, including general market analyses. The Joint Research Centre of the European Commission has previously addressed (Arsenis et al., 2015) the trade price estimation problem by considering data for fixed product, origin and destination over a multiannual time period, typically of 3 or 4 years, leading to price estimates that are specific for each EU Member State. This report illustrates a different model whereby each price estimate is calculated on a monthly basis, using data for fixed time (month), product and origin. The approach differentiates between trades originated from different third countries and it is therefore particularly useful to monitor trends and anomalies in specific EU trade markets. These Estimated European Monthly Prices are publishes every month by the Joint Research Centre in a dedicated section of the THESEUS website (https://theseus.jrc.ec.europa.eu), accessible by authorized users of the EU and Member States services. The section, called Monthly Fair Prices, also shows the time evolution of worldwide price estimates computed with the same approach by fixing only time and product.JRC.I.3-Text and Data Minin

Calibration and Sensitivity Analysis of a Stereo Vision-Based Driver Assistance System

Az http://intechweb.org/ alatti "Books" fül alatt kell rákeresni a "Stereo Vision" címre és az 1. fejezetre

Iterative re-weighted multilinear partial least squares modelling for robust predictive modelling

publishedVersio

Editorial, special issue on “Advances in Robust Statistics”

Starting with 2020 volume, the journal Metron has decided to celebrate the centenary since its foundation with three special issues. This volume is dedicated to robust statistics. A striking feature of most applied statistical analyses is the use of methods that are well known to be sensitive to outliers or to other departures from the postulated model. Robust statistical methods provide useful tools for reducing this sensitivity, through the detection of the outliers by first fitting the majority of the data and then by flagging deviant data points. The six papers in this issue cover a wide orientation in all fields of robustness. This editorial first provides some facts about the history and current state of robust statistics and then summarizes the contents of each paper.status: publishe

MUNICIPALITY DISAGGREGATION OF GERMAN'S AGRICULTURAL SECTOR MODEL RAUMIS

Since several decades the RAUMIS modelling system is applied for policy impact assessments to measure the impact of agriculture on the environment. A disaggregation at the municipality level with more than 9.000 administrative units, instead of currently used 316 counties, would tremendously improve the environmental impact analysis. Two sets of data are used for this purpose. The first are geo-referenced data, that are, however, incomplete with respect its coverage of production activities in agriculture. The second set is the micro census statistic itself, that has a full coverage, but data protection rules (DPR) prohibit its straightforward use. The paper show how this bottleneck can be passed to obtain a reliable modelling data set at municipality level with a complete coverage of the agricultural sector in Germany. We successfully applied a Bayesian estimator, that uses prior information derived a cluster analysis based on the micro census and GIS information. Our test statistics of the estimation, calculated by the statistical office, comparing our estimates and the real protected data, reveals that the proposed approach adequately estimates most activities and can be used to fed the municipality layer in the RAUMIS modelling system for an extended policy analysis.Highest Posterior Density estimator (HPD), RAUMIS, Down scaling, Agricultural and Food Policy, C11, C61, C81, Q15,