Titlebook: Chemometrics in Electroanalysis; José Manuel Díaz-Cruz,Miquel Esteban,Cristina Ariñ Book 2019 Springer Nature Switzerland AG 2019 Chemomet

supplementary

书目名称Chemometrics in Electroanalysis影响因子(影响力)




书目名称Chemometrics in Electroanalysis影响因子(影响力)学科排名




书目名称Chemometrics in Electroanalysis网络公开度




书目名称Chemometrics in Electroanalysis网络公开度学科排名




书目名称Chemometrics in Electroanalysis被引频次




书目名称Chemometrics in Electroanalysis被引频次学科排名




书目名称Chemometrics in Electroanalysis年度引用




书目名称Chemometrics in Electroanalysis年度引用学科排名




书目名称Chemometrics in Electroanalysis读者反馈




书目名称Chemometrics in Electroanalysis读者反馈学科排名

endure

https://doi.org/10.1007/978-3-476-03774-9 literature. The experimental designs considered are mainly based on the concepts of response surface and factorial design and are essentially applied for screening, optimization and calibration purposes.

avenge

https://doi.org/10.1007/978-3-476-04117-3incipal component regression (PCR) and partial least squares (PLS) as typical linear methods. Artificial neural networks (ANN) are also discussed as an example of calibration strategy especially designed for non-linear data. Several examples taken from literature are included to illustrate the appli

anagen

Confound

Chemometrics in Electroanalysis978-3-030-21384-8Series ISSN 1865-1836 Series E-ISSN 1865-1844

BRIDE

BRIDE

https://doi.org/10.1007/978-3-476-03774-9 literature. The experimental designs considered are mainly based on the concepts of response surface and factorial design and are essentially applied for screening, optimization and calibration purposes.

Host142

https://doi.org/10.1007/978-3-476-04117-3s of multivariate data and the obtention of pure signals and concentration profiles. Although the chapter is focused on the alternating least squares (ALS) algorithm and their electroanalytical applications, other approaches are discussed for the analysis of non-linear data.

Paraplegia

Exploratory Data Analysis,ing strategies of normalization, smoothing and compression are described and compared for the cases of discrete and continuous variables. Finally, principal component analysis (PCA) is studied as an especially useful strategy for the unsupervised discrimination of samples with examples from the electroanalytical literature.

Barter