Journal ArticleDOI
PLS-regression: a basic tool of chemometrics
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TLDR
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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Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing
TL;DR: In this article, a combination of two artificial intelligence technologies, namely the radial basis function (RBF) neural network architecture and a specially designed GA, was used for developing nonlinear time series sales forecasting models.
Journal ArticleDOI
Cell culture metabolomics: applications and future directions.
Miroslava Cuperlovic-Culf,Miroslava Cuperlovic-Culf,David Barnett,Adrian S. Culf,Ian C. Chute +4 more
TL;DR: Some of the applications of metabolomics in cell culture analysis and some of the issues that need to be addressed to make this approach more relevant are outlined.
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High-Throughput Phenotyping of Maize Leaf Physiological and Biochemical Traits Using Hyperspectral Reflectance.
Craig R. Yendrek,Tiago Tomaz,Christopher M. Montes,Youyuan Cao,Alison M. Morse,Patrick J. Brown,Lauren M. McIntyre,Andrew D. B. Leakey,Elizabeth A. Ainsworth +8 more
TL;DR: The hyperspectral reflectance approach to phenotyping was dramatically faster than traditional measurements, enabling over 1,000 rows to be phenotyped during midday hours over just 2 to 4 d, and offers a nondestructive method to accurately assess physiological and biochemical trait responses to environmental stress.
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libPLS: An integrated library for partial least squares regression and linear discriminant analysis
TL;DR: The libPLS project as discussed by the authors provides an integrated platform for developing PLS regression and/or linear discriminant analysis (PLS-LDA) models, which can be used to assess, outlier detection, and variable selection.
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Modeling the hydrological impacts of land use/land cover changes in the Andassa watershed, Blue Nile Basin, Ethiopia
TL;DR: The results showed that there was a continuous expansion of cultivated land and built-up area, and withdrawing of forest, shrubland and grassland during the 1985-2015 periods, which are expected to continue in the 2030 and 2045 periods.
References
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Book
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.