13 papers · ranked by Valyu relevance
Samyajoy Pal, Christian Heumann, Sheetal Kalyani
A model-based clustering method for compositional data is explored in this article. Most methods for compositional data analysis require some kind of transformation. The proposed method builds a mixture model using Dirichlet distribution which works with the unit sum constraint. The mixture model uses a hard EM…
Abel Ruiz-Giralt, Stefano Biagetti, Carla Lancelotti, Óscar Parque + 4 more
Anthropic Activity Markers (AAMs) were formalized over 10 years ago as a toolkit to infer human activities from biological and geochemical signatures preserved in sediments. This paper presents AAMs 2.0, a revised analytical framework that integrates compositional data analysis (CoDA) and geostatistics, as the…
Jeseok Lee, Byungwon Kim, Hongchuan Yu
Through the Human Microbiome Project, research on human-associated microbiomes has been conducted in various fields. New sequencing techniques such as Next Generation Sequencing (NGS) and High-Throughput Sequencing (HTS) have enabled the inclusion of a wide range of features of the microbiome. These advancements have…
Viktorie Nesrstová, Ines Wilms, Karel Hron, Peter Filzmoser
Compositional data are characterized by the fact that their elemental information is contained in simple pairwise logratios of the parts that constitute the composition. While pairwise logratios are typically easy to interpret, the number of possible pairs to consider quickly becomes too large even for medium-sized…
Junseop Oh, Kyoung-Ho Kim, Ho-Rim Kim, Sunhwa Park + 1 more
This study introduces a novel groundwater pollution index (GPI) formulated through compositional data analysis (CoDa) and robust principal component analysis (RPCA) to enhance groundwater quality assessment. Using groundwater quality monitoring data from sites impacted by the 2010-2011 foot-and-mouth disease outbreak…
Teo Nguyen, Kerrie Mengersen, Damien Sous, Benoit Liquet + 1 more
'Sathishkumar V E'] Compositional data are a special kind of data, represented as a proportion carrying relative information. Although this type of data is widely spread, no solution exists to deal with the cases where the classes are not well balanced. After describing compositional data imbalance, this paper proposes…
Marco Cruz-Sandoval, José Carlos Vázquez-Parra, Martina Carlos-Arroyo
This article describes a study that sought to identify the correlation between social entrepreneurship and complex thinking competencies in a population of Mexican students. The article uses the novel approach of compositional data analysis. Compositional data analysis focuses on studying data that are part of a whole…
Jesse Pasanen, Tuija Leskinen, Kristin Suorsa, Anna Pulakka + 3 more
'Joni Virta' 'Kari Auranen' 'Sari Stenholm'] We utilized compositional data analysis (CoDA) to study changes in the composition of the 24-h movement behaviors during an activity tracker based physical activity intervention. A total of 231 recently retired Finnish retirees were randomized into intervention and control…
Jingjing Ma, Dinesh Kumar Nishad
To improve the prediction accuracy of compositional data time series (CDTSs), the aggregation of compositional data was considered and applied to construct a combination forecasting model. Different from current arithmetic mean based aggregation of compositional data, the aggregation method of compositional data from…
Sakshi Handa, Kristin K. Isaacs, Jonathan T. Wall, Allison Larger + 8 more
'Scott Burns' 'Lauren E. Koval' 'Kenta Baron-Furuyama' 'Colleen M. Elonen' 'David Lyons' 'Kathie L. Dionisio' 'M. Beth Horton' 'Katherine A. Phillips'] Since the initial release of the Chemical and Products Database (CPDat) in 2018, the United States Environmental Protection Agency has added a considerable amount of…
Stephen A. Allegri, Kevin McCoy, Cassie S. Mitchell
Large networks are quintessential to bioinformatics, knowledge graphs, social network analysis, and graph-based learning. CompositeView is a Python-based open-source application that improves interactive complex network visualization and extraction of actionable insight. CompositeView utilizes specifically formatted…
Xi Yu, Florian Schuberth, Jörg Henseler
Composites, which refer to weighted linear combinations of variables, are receiving increasing attention in the field of ecology. In practice, however, researchers relying on the common approaches to study composites encounter limitations in flexibly specifying composites with structural equation modeling (SEM). To…
Lea Seep, Paul Jonas Jost, Clivia Lisowski, Hao Huang + 9 more
The generation of vast amounts of bulk-omics data has become a common practice. The data analysis often greatly benefits from collaborative efforts between experimental (data generator) and computational (data analyst) researchers as complementary expertise is needed in bioinformatics practices (). Particularly during…