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Showing 1 to 20 of 42 for “"Compositional Data"”.
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Estimating phytoplankton growth rates from compositional data
… Sosik et al., then test this model with a set of data from a laboratory culture whose population growth rate was independently determined. In general, the parameter estimates I obtain for simulated data are better the lower the levels of stochasticity. Despite large confidence intervals around …
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Assessing Inter-rater Agreement for Compositional Data
Compositional data are non-negative vectors whose elements sum to one (e.g., [0.1, 0.5, 0.4]). This type of data occurs in many research areas where the relative magnitudes between the vector’s elements are of primary interest. In this dissertation we propose novel methodology for assessing …
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Estimating phytoplankton growth rates from compositional data
… Sosik et al., then test this model with a set of data from a laboratory culture whose population growth rate was independently determined. In general, the parameter estimates I obtain for simulated data are better the lower the levels of stochasticity. Despite large confidence intervals around …
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On Compositional Data Modeling and Its Biomedical Applications
Compositional data occur naturally in biomedical studies which investigate changes in the proportions of various components of a combined medical measurement. The statistical method to analyze this type of data is underdeveloped. Currently the multivariate logitnormal model seems to be the only …
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Multivariate geostatistical simulation of compositional data using Principal Component Analysis
… spatial processes to model spatially collected data. For the multivariate observations, we should model associations at a specific location and between locations, but also among variables. Common methods for multivariate modeling rely on the Linear Model of Coregionalization (LCM), which is …
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Bayesian Balance Regression And Mediation Analysis For Microbiome Compositional Data
… dance of a microbial community. The resulting data are counts of amplicons. However, the total count is not informative because of the sampling, sample preparation and sequencing processes. These counts are used to obtain estimates of the relative abundance of the taxa, which is com- positional …
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Statistical Modeling for High-dimensional Compositional data with Applications to the Human Microbiome
<p>Compositional data refer to the data that lie on a simplex, which are common in many scientific domains such as genomics, geology, and economics. As the components in a composition must sum to one, traditional tests based on unconstrained data become inappropriate, and new statistical methods …
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Improving the efficiency of modelling complex physical activity data using longitudinal compositional data analysis
Physical activity (PA) data are often objectively collected using an accelerometer worn by the participant, with data collected over a pre-specified period. PA has historically been summarised as a single numerical measure, often the number of minutes spent in moderate-to-vigorous PA, disregarding …
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What is measured is managed : statistical analysis of compositional data towards improved materials recovery
… different types of waste were calculated from data collected by sorting and weighing waste samples from municipal sites. This algorithm recognizes the compositional nature of mass fraction waste data. The algorithm developed in this work also evaluated the value of additional waste samples in …
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Documenting Magnatic Processes at Filicudi Island, Aeolian Arc, Italy: Integrating Quantitative Modeling and Plagioclase Textural and in situ Compositional Data
… eruption styles and managing volcanic hazards. Compositional diversity of magmas develops through recharge, assimilation, and fractional crystallization (RAFC) within subvolcanic magma reservoirs. Integration of MELTS modeling, whole rock, plagioclase textural and in situ elemental and isotopic …
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Compositional observations and their role in regression
… examines the properties and some of the uses of compositional data. It gives a brief history of the distinction between 'normal' data and compositions, as well as the various methods of analysing compositional data. It is mainly concerned with performing regression analysis including …
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On the spatial modelling of mixed and constrained geospatial data
… and spatial relationships, categorical data such as rock types, soil types, alteration units, and continental crustal blocks should be modelled jointly with other continuous attributes (e.g. porosity, permeability, seismic velocity, mineral and geochemical compositions or pollutant …
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PERFORMANCE OF THE TWO SAMPLE LIKELIHOOD RATIO TEST UNDER A NESTED DIRICHLET: A SIMULATION STUDY
<p>Compositional data analysis (CoDA) addresses multivariate data constrained to a constant sum, such as proportions or percentages. Originating from early warnings regarding misinterpretation by Pearson (1897), the field was formalized by John Aitchison in 1986, whose foundational work remains …
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Dynamics of ash eruptions at Vesuvius
… study we present morphological, textural and compositional data on the products of two ash eruptions representative of the whole variability of this activity at Vesuvius (Italy), occurred in the periods between the “Avellino” and “Pompeii” Pumice eruptions (AP3, 2,710±60 years B.P.) and after …
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Investigating Aerosol Composition with Low Cost Optical Particle Counters
… Access to source attribution and compo-sitional data of PM can have many benefits from easier regulation to enabling a better understanding of the negative health effects associated with PM. Acquiring composi-tional data for ambient PM generally has a high associated cost and is done using …
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Geochemical modeling-based prediction of water-rock interaction during aquifer storage and recovery utilizing selected Colorado Front Range aquifers
… Aquifer Storage and Recovery (ASR) targets. Compositional data from surface rock samples, including major, minor and trace elements from bulk rock geochemical analysis and mineral identification from petrography are used to infer a generalized mineral suite to represent each of the formations …
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Compositional models for mutational signature analysis
… that I address, have a characteristic: they are compositional data, because we are interested in studying their relative contribution to the total mutation load. Because of this, they have to be analysed in a multivariate way and in relative terms. Approach: I introduce appropriate compositional …
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Virtually Alone: Exploring the Effects of Technology and Job Design on Loneliness in Remote Work Arrangements
… to workplace loneliness. To complement this, data was also collected on which information communication technology (ICT) employees use most often. A total of 305 employees from the three work models were surveyed. The results showed that as virtuality of the work arrangement increased so did …
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Compositional Associations of Time Spent in Sleep, Screen Time, and Physical Activity with Polysubstance Use in Adolescents
… products, alcohol, cannabis, and illicit drugs. Compositional data analysis was used to investigate relationships between the movement behavior composition and its components with high polysubstance use. Compositional isotemporal substitutions estimated how relocating time from one movement …
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Facies and provenance analysis of the Midcontinent Rift System (MRS) in Kansas
… based on the available geochronological and compositional data, the rift succession in KS seems to be more compatible with post-rift successions elsewhere.
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