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

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書(shū)目名稱(chēng)Chemometrics in Electroanalysis影響因子(影響力)




書(shū)目名稱(chēng)Chemometrics in Electroanalysis影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Chemometrics in Electroanalysis網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Chemometrics in Electroanalysis網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Chemometrics in Electroanalysis被引頻次




書(shū)目名稱(chēng)Chemometrics in Electroanalysis被引頻次學(xué)科排名




書(shū)目名稱(chēng)Chemometrics in Electroanalysis年度引用




書(shū)目名稱(chēng)Chemometrics in Electroanalysis年度引用學(xué)科排名




書(shū)目名稱(chēng)Chemometrics in Electroanalysis讀者反饋




書(shū)目名稱(chēng)Chemometrics in Electroanalysis讀者反饋學(xué)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