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A Comparison of Classical and Bayesian Interval Estimation for Long-Term Indicators of Road Traffic Noise

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The Bayesian model (BAY model) has been compared with interval estimation algorithms of the classical (parametric) statistics assuming that the standard deviation of the population is either known ( k model) or unknown ( u model). A theoretical basis of the proposed model is presented as well as an example of calculation process which makes possible determining confidence intervals of the expected value of long-term noise indicators L DEN and L N. All calculations and implementation of algorithms have been made in the Matlab software. The statistical analysis was carried out for 95% interval widths obtained by using each of these models. The inference of their usefulness to the type A standard uncertainty evaluation of long- term noise indicators was performed on the basis of results of non- parametric statistical tests at significance level α = 0.05. The simulation experiment showed that the width differences of confidence intervals are statistically significant for all three models. The BAY algorithm is characterised by a high degree of coverage of the measured (actual) value. This method can be successfully applied to a small random sample not having any asymptotic properties. The Bayesian intervals are asymmetric with respect to the point estimate in contrast to other described models. Moreover, the confidence intervals obtained using the k model have a constant width. The data used to illustrate the proposed solutions and carry out the analysis were results of continuous monitoring of traffic noise recorded in 2009 in one of the main arteries of Krakow in Poland.
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Document Type: Research Article

Publication date: November 1, 2018

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  • Acta Acustica united with Acustica, published together with the European Acoustics Association (EAA), is an international, peer-reviewed journal on acoustics. It publishes original articles on all subjects in the field of acoustics, such as general linear acoustics, nonlinear acoustics, macrosonics, flow acoustics, atmospheric sound, underwater sound, ultrasonics, physical acoustics, structural acoustics, noise control, active control, environmental noise, building acoustics, room acoustics, acoustic materials, acoustic signal processing, computational and numerical acoustics, hearing, audiology and psychoacoustics, speech, musical acoustics, electroacoustics, auditory quality of systems. It reports on original scientific research in acoustics and on engineering applications. The journal considers scientific papers, technical and applied papers, book reviews, short communications, doctoral thesis abstracts, etc. In irregular intervals also special issues and review articles are published.
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