Bayesian-multiplicative treatment of count zeros in compositional data sets

By Josep-Antoni Martín-Fernández, Karel Hron, Matthias Templ, Peter Filzmoser, J. Palarea‐Albaladejo. 2015

227 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/24e4ef5b9b5fd042769274c9f968a5b349dddaca

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Vera Pawlowsky-Glahn
2. Juan José Egozcue
3. Karel Hron
4. Josep-Antoni Martín-Fernández
5. Peter Filzmoser
6. K. Gerald van den Boogaart
7. Matthias Templ
8. G. Mateu-Figueras

In Environmental Engineering

1. Vera Pawlowsky-Glahn
2. Juan José Egozcue
3. Karel Hron
4. Peter Filzmoser
5. Josep-Antoni Martín-Fernández
6. Matthias Templ
7. J. Palarea‐Albaladejo
8. K. Gerald van den Boogaart

In Media Technology

1. Juan José Egozcue
2. Vera Pawlowsky-Glahn
3. K. Gerald van den Boogaart
4. J. Aitchison

Citations in the corpus

• Compositional data: the sample space and its structure (2019, methodology): “…methods, from hot deck imputation (Martín-Fernández et al. 2003; Fry et al. 2000), imputation based on the dependence structure of the data (Martín-Fernández et al. 2012), to multiple imputation techniques (Palarea-Albaladejo and Martín-Fernández 2008; Palarea-Albaladejo and Martín-Fernández 2015).”
• NetCoMi: network construction and comparison for microbiome data in R (2020, unknown): “[44]: • Parametric • Observed counts c = (c1, .”