Multivariate statistics and hydrogeochemistry of deep groundwater at southwestern part of Bangladesh. [PDF]
Heliyon, 2022 Das TK +4 more
europepmc +1 more source
Multivariate Statistics Tests for Statistics Problem-Solving Performance.
, 2015 Multivariate Statistics Tests for Statistics Problem-Solving Performance.
Ahmad Fauzi Mohd Ayub (763888) +3 more
core +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Applied Multivariate Statistics with R
Journal of Statistical Software, 2016 David W. Zeitler
doaj +1 more source
The search for plausible economic mineral deposits in the central parts of Tanzania; insight from stream sediment geochemistry, multivariate statistics and geostatistics. [PDF]
Heliyon, 2023 Nunoo S, Mvile BN, Abu M, Kelimenze JD.
europepmc +1 more source
Diagnostics and robust estimation in multivariate data transformations [PDF]
, 1993 This paper presents a method for detecting multivariate outliers which might be distorting theı estimation of a transformation to normality.
Velilla Cerdan, Santiago +1 more
core
On Singular Multivariate Normal Distribution and Its Applications
, 1996 10.1016/0167-9473(95)00050-XComputational Statistics and Data Analysis223271 ...
KWONG, Koon Shing +3 more
core +1 more source
An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials
Advanced Engineering Materials, EarlyView.An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut +16 more
wiley +1 more source
Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Improved identification of pollution source attribution by using PAH ratios combined with multivariate statistics. [PDF]
Sci Rep, 2022 Mali M +5 more
europepmc +1 more source