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Mathematics in Education, Research and Applications (MERAA), 2019(5), 1


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Published online 2019-10-15
DOI:https://doi.org/10.15414/meraa.2019.05.01.1-8

Nonparametric distribution of the daylight factor

Dušan Páleš, Milada Balková
Slovak University of Agriculture in Nitra, Slovak Republic

Article Fulltext (PDF), pp. 1–8

Kernel density estimation (KDE) approximates the distribution of statistical data similar to the histogram. The histogram of data is a special kind of the Kernel density. In the reconstructed building of stall in Oponice (Slovakia), we measured the values of daylight factor. The obtained data proved a bimodal distribution, so it was not appropriate to use some of the usual parametric distributions. This paper describes how Kernel density can be applied to measured results. We find out the values of the cumulative distribution function of such density, by probability procedures, that serves us comparison with the prescribed values of the daylight factor in the standard, on the one hand for animals (1.0%) and on the other hand for the people (1.5%) who care for animals. The results obtained from the measurements and the same ones approximated by KDE are in good agreement.

Keywords: Kernel density estimation, bandwidth, daylight factor
JEL Classification: C13, C16