Journal ArticleDOI
PLS-regression: a basic tool of chemometrics
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PLS-regression (PLSR) as mentioned in this paper is the PLS approach in its simplest, and in chemistry and technology, most used form (two-block predictive PLS) is a method for relating two data matrices, X and Y, by a linear multivariate model.About:
This article is published in Chemometrics and Intelligent Laboratory Systems.The article was published on 2001-10-28. It has received 7861 citations till now. The article focuses on the topics: Partial least squares regression.read more
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NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms
Kerry Cawse-Nicholson,Philip A. Townsend,David S. Schimel,Ali M. Assiri,Pamela L. Blake,Maria Fabrizia Buongiorno,Petya K. E. Campbell,Nimrod Carmon,Kimberly A. Casey,Rosa Elvira Correa-Pabón,Kyla M. Dahlin,Hamid Dashti,Philip E. Dennison,Heidi M. Dierssen,Adam Erickson,Joshua B. Fisher,Robert Frouin,Charles K. Gatebe,Hamed Gholizadeh,Michelle M. Gierach,Nancy F. Glenn,Nancy F. Glenn,James A. Goodman,Daniel M. Griffith,Daniel M. Griffith,Liane S. Guild,Christopher R. Hakkenberg,Eric J. Hochberg,Thomas R. H. Holmes,Chuanmin Hu,Glynn Hulley,Karl F. Huemmrich,Karl F. Huemmrich,Raphael M. Kudela,Raymond F. Kokaly,Christine Lee,Roberta E. Martin,Charles E. Miller,Wesley J. Moses,Frank E. Muller-Karger,Joseph D. Ortiz,D. B. Otis,Nima Pahlevan,T. H. Painter,Ryan Pavlick,Ben Poulter,Yi Qi,Vincent Realmuto,Dar A. Roberts,Michael E. Schaepman,Fabian D. Schneider,Florian M. Schwandner,Shawn P. Serbin,Alexey N. Shiklomanov,E. Natasha Stavros,E. Natasha Stavros,David R. Thompson,J. L. Torres-Perez,Kevin R. Turpie,Kevin R. Turpie,Maria Tzortziou,Maria Tzortziou,Susan L. Ustin,Qian Yu,Yusri Yusup,Qingyuan Zhang,Qingyuan Zhang +66 more
TL;DR: The 2017-2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a "designated targeted observable" (DO) as discussed by the authors.
Journal ArticleDOI
High-throughput manufacturing of size-tuned liposomes by a new microfluidics method using enhanced statistical tools for characterization
Elisabeth Kastner,Randip Kaur,Deborah Lowry,Behfar Moghaddam,Alexander Wilkinson,Yvonne Perrie +5 more
TL;DR: This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes and the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.
Journal ArticleDOI
UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: effect of experimental artefacts and anticoagulant
Thaer Barri,Lars O. Dragsted +1 more
TL;DR: Hemparin plasma or serum should be the order of best choice for LC-ESI/MS-based metabolomics research and Citrate and EDTA should be avoided since interferences and serious matrix effects were encountered on some co-eluting polar metabolites.
Book
Model-Based Clustering and Classification for Data Science
TL;DR: In this paper, the authors frame cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions, such as how many clusters are there? which method should I use? How should I handle outliers.
Journal ArticleDOI
MixMC: A Multivariate Statistical Framework to Gain Insight into Microbial Communities.
Kim-Anh Lê Cao,Mary-Ellen Costello,Vanessa Anne Lakis,Francois Bartolo,Xin-Yi Chua,Rémi Brazeilles,Pascale Rondeau +6 more
TL;DR: MixMC as discussed by the authors is a multivariate data analysis framework for metagenomic biomarker discovery, which accounts for the compositional nature of 16S data and enables detection of subtle differences when high inter-subject variability is present due to microbial sampling performed repeatedly on the same subjects, but in multiple habitats.
References
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Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
TL;DR: In this article, the authors present a method for detecting and assessing Collinearity of observations and outliers in the context of extensions to the Wikipedia corpus, based on the concept of Influential Observations.
Book
A User's Guide to Principal Components
TL;DR: In this paper, the authors present a directory of Symbols and Definitions for PCA, as well as some classic examples of PCA applications, such as: linear models, regression PCA of predictor variables, and analysis of variance PCA for Response Variables.
Journal ArticleDOI
A Leisurely Look at the Bootstrap, the Jackknife, and Cross-Validation
Bradley Efron,Gail Gong +1 more
TL;DR: This paper reviewed the nonparametric estimation of statistical error, mainly the bias and standard error of an estimator, or the error rate of a prediction rule, at a relaxed mathematical level, omitting most proofs, regularity conditions and technical details.