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Determining the Number of Measurements and Bootstrap Samples Required to Estimate of Long-Term Noise Indicators

Stępień Bartłomiej

Archives of Acoustics

2020

Vol. 45, No. 4

613--623

The minimum size of the bootstrap algorithm input parameters have been determined for estimation of long-term indicators of road traffic noise. Two independent simulation experiments have been performed for that purpose. The first experiment served to determine the impact of original random sample size, and the second to determine the impact of number of the bootstrap replications on the accuracy and uncertainty of estimation of long-term noise indicators. The inference has been carried out based on results of non-parametric statistical test at significance level α = 0:05. The simulation experiments have shown that estimation of long-term noise indicators with uncertainty below ±1 dB(A) requires all-day noise measurements during three randomly selected days during the year in a dense urban development. The maximum size of original random sample should not exceed n = 50 elements. The minimum number of bootstrap replications necessary for estimation should be B = 5000. The data used to the simulation experiments and carry out the analysis were results of continuous monitoring of road traffic noise recorded in 2009 in one of the main arteries of Krakow in Poland.