Compositional Scalar-on-Function Regression with Application to Sediment Particle Size Distributions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388980%3A_____%2F21%3A00542305" target="_blank" >RIV/61388980:_____/21:00542305 - isvavai.cz</a>

Alternative codes found

RIV/61989592:15310/21:73610049

Result on the web

<a href="http://hdl.handle.net/11104/0322722" target="_blank" >http://hdl.handle.net/11104/0322722</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11004-021-09941-1" target="_blank" >10.1007/s11004-021-09941-1</a>

Result language

angličtina

Original language name

Compositional Scalar-on-Function Regression with Application to Sediment Particle Size Distributions

Original language description

The chemical composition of sediments is controlled predominantly by the sediment grain size, and thus evaluating their relationship is an important task in sedimentary geochemistry. The grain size is characterized by the respective particle size distribution, which can be expressed as a probability density function. Because of the relative character of densities, the Bayes space methodology was employed to build a regression model between a real response and a density function as a covariate, here the chemical composition and the particle size density. For practical computations, density functions were expressed in the standard L-2 space using the centred logratio transformation and spline approximation of the input discretized densities was utilized by respecting the induced zero-integral constraint. After a concise simulation study, supporting the relevance of the proposed regression model, the new methodology was applied to examine the relationship between sediment grain size and geochemical composition, with samples being obtained in the Czech Republic in the Skalka Reservoir and in the Oh.re River floodplain upstream of the reservoir, to reveal proper grain size proxies. The Al/Si and Zr/Rb logratios in the sediments that were studied showed grain-size control, which makes them suitable for this purpose.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10511 - Environmental sciences (social aspects to be 5.7)

Project

<a href="/en/project/GA19-01768S" target="_blank" >GA19-01768S: Separation of geochemical signals in sediments: application of advanced statistical methods on large geochemical datasets</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Mathematical Geosciences

ISSN

1874-8961

e-ISSN

1874-8953

Volume of the periodical

53

Issue of the periodical within the volume

7

Country of publishing house

DE - GERMANY

Number of pages

29

Pages from-to

1667-1695

UT code for WoS article

000642867300001

EID of the result in the Scopus database

2-s2.0-85105144756