Chemometrics : data driven extraction for science / / Richard G. Brereton |
Autore | Brereton Richard G. |
Edizione | [Second edition.] |
Pubbl/distr/stampa | Hoboken, New Jersey ; ; Chichester, West Sussex, England : , : Wiley, , 2018 |
Descrizione fisica | 1 online resource (460 pages) : color illustrations, tables |
Disciplina | 543.015195 |
Soggetto topico |
Chemometrics - Data processing
Chemical processes - Statistical methods - Data processing |
Soggetto genere / forma | Electronic books. |
ISBN |
1-118-90468-0
1-118-90467-2 1-118-90469-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910271043703321 |
Brereton Richard G. | ||
Hoboken, New Jersey ; ; Chichester, West Sussex, England : , : Wiley, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Chemometrics : data driven extraction for science / / Richard G. Brereton |
Autore | Brereton Richard G. |
Edizione | [Second edition.] |
Pubbl/distr/stampa | Hoboken, New Jersey ; ; Chichester, West Sussex, England : , : Wiley, , 2018 |
Descrizione fisica | 1 online resource (460 pages) : color illustrations, tables |
Disciplina | 543.015195 |
Soggetto topico |
Chemometrics - Data processing
Chemical processes - Statistical methods - Data processing |
ISBN |
1-118-90468-0
1-118-90467-2 1-118-90469-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910830008303321 |
Brereton Richard G. | ||
Hoboken, New Jersey ; ; Chichester, West Sussex, England : , : Wiley, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Chemometrics [[electronic resource] ] : data analysis for the laboratory and chemical plant / / Richard Brereton |
Autore | Brereton Richard G |
Pubbl/distr/stampa | Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 |
Descrizione fisica | 1 online resource (505 p.) |
Disciplina |
540.151
543.0015195 |
Soggetto topico |
Chemometrics - Data processing
Chemical processes - Statistical methods - Data processing |
Soggetto genere / forma | Electronic books. |
ISBN |
9786610269686
0-470-66760-5 0-470-86324-2 1-280-26968-5 0-470-84574-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Chemometrics; Contents; Preface; Supplementary Information; Acknowledgements; 1 Introduction; 1.1 Points of View; 1.2 Software and Calculations; 1.3 Further Reading; 1.3.1 General; 1.3.2 Specific Areas; 1.3.3 Internet Resources; 1.4 References; 2 Experimental Design; 2.1 Introduction; 2.2 Basic Principles; 2.2.1 Degrees of Freedom; 2.2.2 Analysis of Variance and Comparison of Errors; 2.2.3 Design Matrices and Modelling; 2.2.4 Assessment of Significance; 2.2.5 Leverage and Confidence in Models; 2.3 Factorial Designs; 2.3.1 Full Factorial Designs; 2.3.2 Fractional Factorial Designs
2.3.3 Plackett-Burman and Taguchi Designs2.3.4 Partial Factorials at Several Levels: Calibration Designs; 2.4 Central Composite or Response Surface Designs; 2.4.1 Setting Up the Design; 2.4.2 Degrees of Freedom; 2.4.3 Axial Points; 2.4.4 Modelling; 2.4.5 Statistical Factors; 2.5 Mixture Designs; 2.5.1 Mixture Space; 2.5.2 Simplex Centroid; 2.5.3 Simplex Lattice; 2.5.4 Constraints; 2.5.5 Process Variables; 2.6 Simplex Optimisation; 2.6.1 Fixed Sized Simplex; 2.6.2 Elaborations; 2.6.3 Modified Simplex; 2.6.4 Limitations; Problems; 3 Signal Processing; 3.1 Sequential Signals in Chemistry 3.1.1 Environmental and Geological Processes3.1.2 Industrial Process Control; 3.1.3 Chromatograms and Spectra; 3.1.4 Fourier Transforms; 3.1.5 Advanced Methods; 3.2 Basics; 3.2.1 Peakshapes; 3.2.2 Digitisation; 3.2.3 Noise; 3.2.4 Sequential Processes; 3.3 Linear Filters; 3.3.1 Smoothing Functions; 3.3.2 Derivatives; 3.3.3 Convolution; 3.4 Correlograms and Time Series Analysis; 3.4.1 Auto-correlograms; 3.4.2 Cross-correlograms; 3.4.3 Multivariate Correlograms; 3.5 Fourier Transform Techniques; 3.5.1 Fourier Transforms; 3.5.2 Fourier Filters; 3.5.3 Convolution Theorem; 3.6 Topical Methods 3.6.1 Kalman Filters3.6.2 Wavelet Transforms; 3.6.3 Maximum Entropy (Maxent) and Bayesian Methods; Problems; 4 Pattern Recognition; 4.1 Introduction; 4.1.1 Exploratory Data Analysis; 4.1.2 Unsupervised Pattern Recognition; 4.1.3 Supervised Pattern Recognition; 4.2 The Concept and Need for Principal Components Analysis; 4.2.1 History; 4.2.2 Case Studies; 4.2.3 Multivariate Data Matrices; 4.2.4 Aims of PCA; 4.3 Principal Components Analysis: the Method; 4.3.1 Chemical Factors; 4.3.2 Scores and Loadings; 4.3.3 Rank and Eigenvalues; 4.3.4 Factor Analysis 4.3.5 Graphical Representation of Scores and Loadings4.3.6 Preprocessing; 4.3.7 Comparing Multivariate Patterns; 4.4 Unsupervised Pattern Recognition: Cluster Analysis; 4.4.1 Similarity; 4.4.2 Linkage; 4.4.3 Next Steps; 4.4.4 Dendrograms; 4.5 Supervised Pattern Recognition; 4.5.1 General Principles; 4.5.2 Discriminant Analysis; 4.5.3 SIMCA; 4.5.4 Discriminant PLS; 4.5.5 K Nearest Neighbours; 4.6 Multiway Pattern Recognition; 4.6.1 Tucker3 Models; 4.6.2 PARAFAC; 4.6.3 Unfolding; Problems; 5 Calibration; 5.1 Introduction; 5.1.1 History and Usage; 5.1.2 Case Study; 5.1.3 Terminology 5.2 Univariate Calibration |
Record Nr. | UNINA-9910143558103321 |
Brereton Richard G | ||
Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Chemometrics [[electronic resource] ] : data analysis for the laboratory and chemical plant / / Richard Brereton |
Autore | Brereton Richard G |
Pubbl/distr/stampa | Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 |
Descrizione fisica | 1 online resource (505 p.) |
Disciplina |
540.151
543.0015195 |
Soggetto topico |
Chemometrics - Data processing
Chemical processes - Statistical methods - Data processing |
ISBN |
9786610269686
0-470-66760-5 0-470-86324-2 1-280-26968-5 0-470-84574-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Chemometrics; Contents; Preface; Supplementary Information; Acknowledgements; 1 Introduction; 1.1 Points of View; 1.2 Software and Calculations; 1.3 Further Reading; 1.3.1 General; 1.3.2 Specific Areas; 1.3.3 Internet Resources; 1.4 References; 2 Experimental Design; 2.1 Introduction; 2.2 Basic Principles; 2.2.1 Degrees of Freedom; 2.2.2 Analysis of Variance and Comparison of Errors; 2.2.3 Design Matrices and Modelling; 2.2.4 Assessment of Significance; 2.2.5 Leverage and Confidence in Models; 2.3 Factorial Designs; 2.3.1 Full Factorial Designs; 2.3.2 Fractional Factorial Designs
2.3.3 Plackett-Burman and Taguchi Designs2.3.4 Partial Factorials at Several Levels: Calibration Designs; 2.4 Central Composite or Response Surface Designs; 2.4.1 Setting Up the Design; 2.4.2 Degrees of Freedom; 2.4.3 Axial Points; 2.4.4 Modelling; 2.4.5 Statistical Factors; 2.5 Mixture Designs; 2.5.1 Mixture Space; 2.5.2 Simplex Centroid; 2.5.3 Simplex Lattice; 2.5.4 Constraints; 2.5.5 Process Variables; 2.6 Simplex Optimisation; 2.6.1 Fixed Sized Simplex; 2.6.2 Elaborations; 2.6.3 Modified Simplex; 2.6.4 Limitations; Problems; 3 Signal Processing; 3.1 Sequential Signals in Chemistry 3.1.1 Environmental and Geological Processes3.1.2 Industrial Process Control; 3.1.3 Chromatograms and Spectra; 3.1.4 Fourier Transforms; 3.1.5 Advanced Methods; 3.2 Basics; 3.2.1 Peakshapes; 3.2.2 Digitisation; 3.2.3 Noise; 3.2.4 Sequential Processes; 3.3 Linear Filters; 3.3.1 Smoothing Functions; 3.3.2 Derivatives; 3.3.3 Convolution; 3.4 Correlograms and Time Series Analysis; 3.4.1 Auto-correlograms; 3.4.2 Cross-correlograms; 3.4.3 Multivariate Correlograms; 3.5 Fourier Transform Techniques; 3.5.1 Fourier Transforms; 3.5.2 Fourier Filters; 3.5.3 Convolution Theorem; 3.6 Topical Methods 3.6.1 Kalman Filters3.6.2 Wavelet Transforms; 3.6.3 Maximum Entropy (Maxent) and Bayesian Methods; Problems; 4 Pattern Recognition; 4.1 Introduction; 4.1.1 Exploratory Data Analysis; 4.1.2 Unsupervised Pattern Recognition; 4.1.3 Supervised Pattern Recognition; 4.2 The Concept and Need for Principal Components Analysis; 4.2.1 History; 4.2.2 Case Studies; 4.2.3 Multivariate Data Matrices; 4.2.4 Aims of PCA; 4.3 Principal Components Analysis: the Method; 4.3.1 Chemical Factors; 4.3.2 Scores and Loadings; 4.3.3 Rank and Eigenvalues; 4.3.4 Factor Analysis 4.3.5 Graphical Representation of Scores and Loadings4.3.6 Preprocessing; 4.3.7 Comparing Multivariate Patterns; 4.4 Unsupervised Pattern Recognition: Cluster Analysis; 4.4.1 Similarity; 4.4.2 Linkage; 4.4.3 Next Steps; 4.4.4 Dendrograms; 4.5 Supervised Pattern Recognition; 4.5.1 General Principles; 4.5.2 Discriminant Analysis; 4.5.3 SIMCA; 4.5.4 Discriminant PLS; 4.5.5 K Nearest Neighbours; 4.6 Multiway Pattern Recognition; 4.6.1 Tucker3 Models; 4.6.2 PARAFAC; 4.6.3 Unfolding; Problems; 5 Calibration; 5.1 Introduction; 5.1.1 History and Usage; 5.1.2 Case Study; 5.1.3 Terminology 5.2 Univariate Calibration |
Record Nr. | UNINA-9910831073603321 |
Brereton Richard G | ||
Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Chemometrics : data analysis for the laboratory and chemical plant / / Richard Brereton |
Autore | Brereton Richard G |
Pubbl/distr/stampa | Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 |
Descrizione fisica | 1 online resource (505 p.) |
Disciplina | 543/.007/27 |
Soggetto topico |
Chemometrics - Data processing
Chemical processes - Statistical methods - Data processing |
ISBN |
9786610269686
0-470-66760-5 0-470-86324-2 1-280-26968-5 0-470-84574-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Chemometrics; Contents; Preface; Supplementary Information; Acknowledgements; 1 Introduction; 1.1 Points of View; 1.2 Software and Calculations; 1.3 Further Reading; 1.3.1 General; 1.3.2 Specific Areas; 1.3.3 Internet Resources; 1.4 References; 2 Experimental Design; 2.1 Introduction; 2.2 Basic Principles; 2.2.1 Degrees of Freedom; 2.2.2 Analysis of Variance and Comparison of Errors; 2.2.3 Design Matrices and Modelling; 2.2.4 Assessment of Significance; 2.2.5 Leverage and Confidence in Models; 2.3 Factorial Designs; 2.3.1 Full Factorial Designs; 2.3.2 Fractional Factorial Designs
2.3.3 Plackett-Burman and Taguchi Designs2.3.4 Partial Factorials at Several Levels: Calibration Designs; 2.4 Central Composite or Response Surface Designs; 2.4.1 Setting Up the Design; 2.4.2 Degrees of Freedom; 2.4.3 Axial Points; 2.4.4 Modelling; 2.4.5 Statistical Factors; 2.5 Mixture Designs; 2.5.1 Mixture Space; 2.5.2 Simplex Centroid; 2.5.3 Simplex Lattice; 2.5.4 Constraints; 2.5.5 Process Variables; 2.6 Simplex Optimisation; 2.6.1 Fixed Sized Simplex; 2.6.2 Elaborations; 2.6.3 Modified Simplex; 2.6.4 Limitations; Problems; 3 Signal Processing; 3.1 Sequential Signals in Chemistry 3.1.1 Environmental and Geological Processes3.1.2 Industrial Process Control; 3.1.3 Chromatograms and Spectra; 3.1.4 Fourier Transforms; 3.1.5 Advanced Methods; 3.2 Basics; 3.2.1 Peakshapes; 3.2.2 Digitisation; 3.2.3 Noise; 3.2.4 Sequential Processes; 3.3 Linear Filters; 3.3.1 Smoothing Functions; 3.3.2 Derivatives; 3.3.3 Convolution; 3.4 Correlograms and Time Series Analysis; 3.4.1 Auto-correlograms; 3.4.2 Cross-correlograms; 3.4.3 Multivariate Correlograms; 3.5 Fourier Transform Techniques; 3.5.1 Fourier Transforms; 3.5.2 Fourier Filters; 3.5.3 Convolution Theorem; 3.6 Topical Methods 3.6.1 Kalman Filters3.6.2 Wavelet Transforms; 3.6.3 Maximum Entropy (Maxent) and Bayesian Methods; Problems; 4 Pattern Recognition; 4.1 Introduction; 4.1.1 Exploratory Data Analysis; 4.1.2 Unsupervised Pattern Recognition; 4.1.3 Supervised Pattern Recognition; 4.2 The Concept and Need for Principal Components Analysis; 4.2.1 History; 4.2.2 Case Studies; 4.2.3 Multivariate Data Matrices; 4.2.4 Aims of PCA; 4.3 Principal Components Analysis: the Method; 4.3.1 Chemical Factors; 4.3.2 Scores and Loadings; 4.3.3 Rank and Eigenvalues; 4.3.4 Factor Analysis 4.3.5 Graphical Representation of Scores and Loadings4.3.6 Preprocessing; 4.3.7 Comparing Multivariate Patterns; 4.4 Unsupervised Pattern Recognition: Cluster Analysis; 4.4.1 Similarity; 4.4.2 Linkage; 4.4.3 Next Steps; 4.4.4 Dendrograms; 4.5 Supervised Pattern Recognition; 4.5.1 General Principles; 4.5.2 Discriminant Analysis; 4.5.3 SIMCA; 4.5.4 Discriminant PLS; 4.5.5 K Nearest Neighbours; 4.6 Multiway Pattern Recognition; 4.6.1 Tucker3 Models; 4.6.2 PARAFAC; 4.6.3 Unfolding; Problems; 5 Calibration; 5.1 Introduction; 5.1.1 History and Usage; 5.1.2 Case Study; 5.1.3 Terminology 5.2 Univariate Calibration |
Record Nr. | UNINA-9910877856003321 |
Brereton Richard G | ||
Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|