2026-04-17T06:19:46Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4717102024-11-04T06:48:20Zcom_2072_98col_2072_378192

00925njm 22002777a 4500 dc Pavlů, Ivana author Menafoglio, Alessandra author Bongiorno, Enea author Hron, Karel author 2023 The process of supervised classification when the data set consists of probability density functions is studied. Due to the relative information contained in densities, it is necessary to convert the functional data analysis methods into an appropriate framework, here represented by the Bayes spaces. This work develops Bayes space counterparts to a set of commonly used functional methods with a focus on classification. Hereby, a clear guideline is provided on how some classification approaches can be adapted for the case of densities. Comparison of the methods is based on simulation studies and real-world applications, reflecting their respective strengths and weaknesses. http://hdl.handle.net/2072/471710 Probability density functions Bayes spaces Classifcation Functional data analysis Classification of probability density functions in the framework of Bayes spaces : methods and applications