{"title":"Nonparametric distribution of the daylight factor","authors":"D. Páleš, M. Balková","doi":"10.15414/meraa.2019.05.01.1-8","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":356304,"journal":{"name":"Mathematics in Education, Research and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematics in Education, Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15414/meraa.2019.05.01.1-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.