Results 21 to 30 of about 8,001,041 (336)
COSIMA data analysis using multivariate techniques [PDF]
Geoscientific Instrumentation, Methods and Data Systems, 2015 We describe how to use multivariate analysis of complex TOF-SIMS (time-of-flight secondary ion mass spectrometry) spectra by introducing the method of random projections.
J. Silén +6 more
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The Use of Multivariate Data Analysis (HCA and PCA) to Characterize Ashes from Biomass Combustion
Energies, 2021 The content of heavy metals Cd, Cr, Cu, Fe, Ni, Pb and Zn in ash samples from miscanthus, oak, pine, sunflower husk, wheat straw, and willow ashes burned at 500, 600, 700, 800, 900, and 1000 °C, respectively, was determined.
Małgorzata Szczepanik +5 more
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St. Petersburg Polytechnical University Journal: Physics and Mathematics, 2021 An algorithm for processing mass spectra of gases exhaled by patients has been proposed in the paper. The mass spectra are recorded on the MS7-200 quadrupole mass spectrometer, with electronic ionization and with direct capillary injection of the sample.
Manoilov vladimir +4 more
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A review on longitudinal data analysis with random forest [PDF]
Briefings Bioinform., 2022 In longitudinal studies variables are measured repeatedly over time, leading to clustered and correlated observations. If the goal of the study is to develop prediction models, machine learning approaches such as the powerful random forest (RF) are often
Jianchang Hu, S. Szymczak
semanticscholar +1 more source
Insight into human pubertal growth by applying the QEPS growth model
BMC Pediatrics, 2017 Background Computerized mathematical models describing absolute and relative individual growth during puberty in both cm and standard deviation (SD)-scores are lacking.
Anton Holmgren +5 more
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Enhancing Speech Emotions Recognition Using Multivariate Functional Data Analysis
Big Data and Cognitive Computing, 2023 Speech Emotions Recognition (SER) has gained significant attention in the fields of human–computer interaction and speech processing. In this article, we present a novel approach to improve SER performance by interpreting the Mel Frequency Cepstral ...
Matthieu Saumard
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Resampling-Based Analysis of Multivariate Data and Repeated Measures Designs with the R Package MANOVA.RM [PDF]
The R Journal, 2018 The numerical availability of statistical inference methods for a modern and robust analysis of longitudinal- and multivariate data in factorial experiments is an essential element in research and education.
Sarah Friedrich +2 more
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Bayesian Semiparametric Regression Analysis of Multivariate Panel Count Data
Stats, 2022 Panel count data often occur in a long-term recurrent event study, where the exact occurrence time of the recurrent events is unknown, but only the occurrence count between any two adjacent observation time points is recorded.
Chunling Wang, Xiaoyan Lin
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Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data [PDF]
Neurons, Behavior, Data analysis, and Theory, 2018 How does one find dimensions in multivariate data that are reliably expressed across repetitions? For example, in a brain imaging study one may want to identify combinations of neural signals that are reliably expressed across multiple trials or subjects.
L. Parra, S. Haufe, J. Dmochowski
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Correlation Analysis for Exploring Multivariate Data Sets
IEEE Access, 2018 Correlation analysis is of great significance for exploring the multivariate data sets as it helps researchers toward an in-depth understanding of the complex interactions and relationships among variables.
Li Wang +3 more
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