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Partial least squares discriminant analysis: taking the magic away

Journal of chemometrics, 2014-04, Vol.28 (4), p.213-225

2014

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Chemometrics for Pattern Recognition

Brereton, Richard G

1, 2009

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Applied Chemometrics for Scientists

Brereton, Richard G

1, 2007

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Ten years of Heritage Science

Heritage science, 2023-11, Vol.11 (1), p.233-5, Article 233

Brereton, Richard G

2023

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Partial least squares discriminant analysis for chemometrics and metabolomics: How scores, loadings, and weights differ according to two common algorithms

Journal of chemometrics, 2018-04, Vol.32 (4), p.n/a

2018

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Re-evaluating the role of the Mahalanobis distance measure

Journal of chemometrics, 2016-04, Vol.30 (4), p.134-143

2016

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Principal components analysis with several objects and variables

Journal of chemometrics, 2023-04, Vol.37 (4), p.n/a

Brereton, Richard G.

2023

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The Mahalanobis distance and its relationship to principal component scores

Journal of chemometrics, 2015-03, Vol.29 (3), p.143-145

Brereton, Richard G.

2015

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Contingency tables, confusion matrices, classifiers and quality of prediction

Journal of chemometrics, 2021-11, Vol.35 (11), p.n/a

Brereton, Richard G.

2021

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Individual and gender fingerprints in human body odour

Journal of the Royal Society interface, 2007-04, Vol.4 (13), p.331

2007

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Five years of Heritage Science: from aborigine cave paintings to the Domesday book and Bayeux tapestry and to Dorothy’s ruby red slippers via van Gogh’s colours, Magritte’s missing quarters, and Qing calligraphy, with the sights, sounds, smells and taste of the past

Heritage science, 2018-11, Vol.6 (1), p.1-3, Article 69

Brereton, Richard G.

2018

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Graphical introduction to principal components analysis

Journal of chemometrics, 2022-06, Vol.36 (6), p.n/a

Brereton, Richard G.

2022

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Numerical introduction to principal components analysis

Journal of chemometrics, 2022-08, Vol.36 (8), p.n/a

Brereton, Richard G.

2022

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Introduction to statistical, algorithmic and theoretical basis of principal components analysis

Journal of chemometrics, 2022-09, Vol.36 (9), p.n/a

Brereton, Richard G.

2022

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Introduction to residuals and estimation by principal components analysis

Journal of chemometrics, 2022-10, Vol.36 (10), p.n/a

Brereton, Richard G.

2022

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Chemometrics: data driven extraction for science

Brereton, Richard G

Second edition., 2018

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Support Vector Machines: A Recent Method for Classification in Chemometrics

Critical reviews in analytical chemistry, 2006-12, Vol.36 (3-4), p.177-188

2006

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Alpha, beta, type 1 and 2 errors, Ergon Pearson and Jerzy Neyman

Journal of chemometrics, 2021-03, Vol.35 (3), p.n/a

Brereton, Richard G.

2021

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Introduction to Bayesian methods

Journal of chemometrics, 2022-01, Vol.36 (1), p.n/a

Brereton, Richard G.

2022

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False discovery rates, power and related concepts

Journal of chemometrics, 2021-06, Vol.35 (6), p.n/a

Brereton, Richard G.

2021

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Multivariate classification models

Journal of chemometrics, 2021-12, Vol.35 (12), p.n/a

Brereton, Richard G.

2021

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The use and misuse of p values and related concepts

Chemometrics and intelligent laboratory systems, 2019-12, Vol.195, p.103884, Article 103884

Brereton, Richard G.

2019

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P values and Ronald Fisher

Journal of chemometrics, 2020-09, Vol.34 (9), p.n/a

Brereton, Richard G.

2020

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Empirical and statistical p values and Type 1 error rates: Putting it all together

Journal of chemometrics, 2021-09, Vol.35 (9), p.n/a

Brereton, Richard G.

2021

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Introduction to analysis of variance

Journal of chemometrics, 2019-01, Vol.33 (1), p.n/a

Brereton, Richard G.

2019

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Partial least squares discriminant analysis: taking the magic away

Chemometrics for Pattern Recognition

Applied Chemometrics for Scientists

Ten years of Heritage Science

Partial least squares discriminant analysis for chemometrics and metabolomics: How scores, loadings, and weights differ according to two common algorithms

Re-evaluating the role of the Mahalanobis distance measure

Principal components analysis with several objects and variables

The Mahalanobis distance and its relationship to principal component scores

Contingency tables, confusion matrices, classifiers and quality of prediction

Individual and gender fingerprints in human body odour

Five years of Heritage Science: from aborigine cave paintings to the Domesday book and Bayeux tapestry and to Dorothy’s ruby red slippers via van Gogh’s colours, Magritte’s missing quarters, and Qing calligraphy, with the sights, sounds, smells and taste of the past

Graphical introduction to principal components analysis

Numerical introduction to principal components analysis

Introduction to statistical, algorithmic and theoretical basis of principal components analysis

Introduction to residuals and estimation by principal components analysis

Chemometrics: data driven extraction for science

Support Vector Machines: A Recent Method for Classification in Chemometrics

Alpha, beta, type 1 and 2 errors, Ergon Pearson and Jerzy Neyman

Introduction to Bayesian methods

False discovery rates, power and related concepts

Multivariate classification models

The use and misuse of p values and related concepts

P values and Ronald Fisher

Empirical and statistical p values and Type 1 error rates: Putting it all together

Introduction to analysis of variance

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