大葉大學圖書館 |

The multiple facets of partial least squares and related methods[electronic resource] :PLS, Paris, France, 2014 /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	511.42
書名/作者:	The multiple facets of partial least squares and related methods : PLS, Paris, France, 2014 // edited by Herve Abdi ... [et al.].
其他作者:	Abdi, Herve.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xiv, 316 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Least squares
標題:	Statistics.
標題:	Statistical Theory and Methods.
標題:	Mathematical Models of Cognitive Processes and Neural Networks.
標題:	Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
ISBN:	9783319406435
ISBN:	9783319406411
內容註:	1. Partial Last Squares for Heterogeneous Data -- 2. On the PLS Algorithm for Multiple Regression (PLS1) -- 3. Extending the Finite Iterative Method for Computing the Covariance Matrix Implied by a Recursive Path Model -- 4. Which Resampling-Based Error Estimator for Benchmark Studies? A Power Analysis with Application to PLS-LDA -- 5. Path Directions Incoherence in PLS Path Modeling: A Prediction-Oriented Solution -- 6. Imaging Genetics with Partial Least Squares for Mixed-Data Types (MiMoPLS) -- 7. PLS and Functional Neuroimaging: Bias and Detection Power Across Different Resampling Schemes -- 8. Estimating and Correcting Optimism Bias in Multivariate PLS Regression: Application to the Study of the Association Between Single Nucleotide Polymorphisms and Multivariate Traits in Attention Deficit Hyperactivity Disorder -- 9. Discriminant Analysis for Multiway Data -- 10. Structured Variable Selection for Regularized Generalized Canonical Correlation Analysis -- 11. Supervised Component Generalized Linear Regression with Multiple Explanatory Blocks: THEME-SCGLR -- 12. Partial Possibilistic Regression Path Modeling -- 13. Assessment and Validation in Quantile Composite-Based Path Modeling -- 14. PLS-Frailty Model for Cancer Survival Analysis Based on Gene Expression Profiles -- 15. Functional Linear Regression Analysis Based on Partial Least Squares and Its Application -- 16. Multiblock and Multigroup PLS Application to Study Cannabis Consumption in Thirteen European Countries -- 17. A Unified Framework to Study the Properties of the PLS Vector of Regression Coefficients -- 18. A New Bootstrap-Based Stopping Criterion in PLS Components Construction -- 19. Extension to the PATHMOX Approach to Detect which Constructs Differentiate Segments and to Test Factor Invariance: Application to Mental Health Data -- 20. Multi-Group Invariance Testing: An Illustrative Comparison of PLS Permutation and Covariance-Based SEM Invariance Analysis -- 21. Brand Nostalgia and Consumers' Relationships to Luxury Brands: A Continuous and Categorical Moderated Mediation Approach -- 22. A Partial Least Squares Algorithm Handling Ordinal Variables.
摘要、提要註:	This volume presents state of the art theories, new developments, and important applications of Partial Least Square (PLS) methods. The text begins with the invited communications of current leaders in the field who cover the history of PLS, an overview of methodological issues, and recent advances in regression and multi-block approaches. The rest of the volume comprises selected, reviewed contributions from the 8th International Conference on Partial Least Squares and Related Methods held in Paris, France, on 26-28 May, 2014. They are organized in four coherent sections: 1) new developments in genomics and brain imaging, 2) new and alternative methods for multi-table and path analysis, 3) advances in partial least square regression (PLSR), and 4) partial least square path modeling (PLS-PM) breakthroughs and applications. PLS methods are very versatile methods that are now used in areas as diverse as engineering, life science, sociology, psychology, brain imaging, genomics, and business among both academics and practitioners. The selected chapters here highlight this diversity with applied examples as well as the most recent advances. Integrates theoretical and methodological advances from recognized leaders in the field, including the conference's invited speakers Important applications in domains such as genomics, brain imaging, sensory analysis, marketing, psychometrics and information systems Covers PLS regression, PLS path modeling and developments that go beyond PLS specific methods, extending to other component-based and multi-block or multi-way methods.
電子資源:	http://dx.doi.org/10.1007/978-3-319-40643-5

The multiple facets of partial least squares and related methods[electronic resource] :PLS, Paris, France, 2014 /
The multiple facets of partial least squares and related methodsPLS, Paris, France, 2014 /[electronic resource] :edited by Herve Abdi ... [et al.]. - Cham :Springer International Publishing :2016. - xiv, 316 p. :ill., digital ;24 cm. - Springer proceedings in mathematics & statistics,v.1732194-1009 ;. - Springer proceedings in mathematics & statistics ;v.70..

1. Partial Last Squares for Heterogeneous Data -- 2. On the PLS Algorithm for Multiple Regression (PLS1) -- 3. Extending the Finite Iterative Method for Computing the Covariance Matrix Implied by a Recursive Path Model -- 4. Which Resampling-Based Error Estimator for Benchmark Studies? A Power Analysis with Application to PLS-LDA -- 5. Path Directions Incoherence in PLS Path Modeling: A Prediction-Oriented Solution -- 6. Imaging Genetics with Partial Least Squares for Mixed-Data Types (MiMoPLS) -- 7. PLS and Functional Neuroimaging: Bias and Detection Power Across Different Resampling Schemes -- 8. Estimating and Correcting Optimism Bias in Multivariate PLS Regression: Application to the Study of the Association Between Single Nucleotide Polymorphisms and Multivariate Traits in Attention Deficit Hyperactivity Disorder -- 9. Discriminant Analysis for Multiway Data -- 10. Structured Variable Selection for Regularized Generalized Canonical Correlation Analysis -- 11. Supervised Component Generalized Linear Regression with Multiple Explanatory Blocks: THEME-SCGLR -- 12. Partial Possibilistic Regression Path Modeling -- 13. Assessment and Validation in Quantile Composite-Based Path Modeling -- 14. PLS-Frailty Model for Cancer Survival Analysis Based on Gene Expression Profiles -- 15. Functional Linear Regression Analysis Based on Partial Least Squares and Its Application -- 16. Multiblock and Multigroup PLS Application to Study Cannabis Consumption in Thirteen European Countries -- 17. A Unified Framework to Study the Properties of the PLS Vector of Regression Coefficients -- 18. A New Bootstrap-Based Stopping Criterion in PLS Components Construction -- 19. Extension to the PATHMOX Approach to Detect which Constructs Differentiate Segments and to Test Factor Invariance: Application to Mental Health Data -- 20. Multi-Group Invariance Testing: An Illustrative Comparison of PLS Permutation and Covariance-Based SEM Invariance Analysis -- 21. Brand Nostalgia and Consumers' Relationships to Luxury Brands: A Continuous and Categorical Moderated Mediation Approach -- 22. A Partial Least Squares Algorithm Handling Ordinal Variables.

This volume presents state of the art theories, new developments, and important applications of Partial Least Square (PLS) methods. The text begins with the invited communications of current leaders in the field who cover the history of PLS, an overview of methodological issues, and recent advances in regression and multi-block approaches. The rest of the volume comprises selected, reviewed contributions from the 8th International Conference on Partial Least Squares and Related Methods held in Paris, France, on 26-28 May, 2014. They are organized in four coherent sections: 1) new developments in genomics and brain imaging, 2) new and alternative methods for multi-table and path analysis, 3) advances in partial least square regression (PLSR), and 4) partial least square path modeling (PLS-PM) breakthroughs and applications. PLS methods are very versatile methods that are now used in areas as diverse as engineering, life science, sociology, psychology, brain imaging, genomics, and business among both academics and practitioners. The selected chapters here highlight this diversity with applied examples as well as the most recent advances. Integrates theoretical and methodological advances from recognized leaders in the field, including the conference's invited speakers Important applications in domains such as genomics, brain imaging, sensory analysis, marketing, psychometrics and information systems Covers PLS regression, PLS path modeling and developments that go beyond PLS specific methods, extending to other component-based and multi-block or multi-way methods.

ISBN: 9783319406435

Standard No.: 10.1007/978-3-319-40643-5doiSubjects--Topical Terms:

168711
Least squares

LC Class. No.: QA275

Dewey Class. No.: 511.42

The multiple facets of partial least squares and related methods[electronic resource] :PLS, Paris, France, 2014 /
LDR:04815nmm a2200325 a 4500 001 467653
003 DE-He213
005 20161013122048.0
006 m d
007 cr nn 008maaau
008 170511s2016 gw s 0 eng d
020 $a 9783319406435 $q (electronic bk.)
020 $a 9783319406411 $q (paper)
024 7 $a 10.1007/978-3-319-40643-5 $2 doi
035 $a 978-3-319-40643-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA275
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 511.42 $2 23
090 $a QA275 $b .M961 2016
245 0 4 $a The multiple facets of partial least squares and related methods $h [electronic resource] : $b PLS, Paris, France, 2014 / $c edited by Herve Abdi ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xiv, 316 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer proceedings in mathematics & statistics, $x 2194-1009 ; $v v.173
505 0 $a 1. Partial Last Squares for Heterogeneous Data -- 2. On the PLS Algorithm for Multiple Regression (PLS1) -- 3. Extending the Finite Iterative Method for Computing the Covariance Matrix Implied by a Recursive Path Model -- 4. Which Resampling-Based Error Estimator for Benchmark Studies? A Power Analysis with Application to PLS-LDA -- 5. Path Directions Incoherence in PLS Path Modeling: A Prediction-Oriented Solution -- 6. Imaging Genetics with Partial Least Squares for Mixed-Data Types (MiMoPLS) -- 7. PLS and Functional Neuroimaging: Bias and Detection Power Across Different Resampling Schemes -- 8. Estimating and Correcting Optimism Bias in Multivariate PLS Regression: Application to the Study of the Association Between Single Nucleotide Polymorphisms and Multivariate Traits in Attention Deficit Hyperactivity Disorder -- 9. Discriminant Analysis for Multiway Data -- 10. Structured Variable Selection for Regularized Generalized Canonical Correlation Analysis -- 11. Supervised Component Generalized Linear Regression with Multiple Explanatory Blocks: THEME-SCGLR -- 12. Partial Possibilistic Regression Path Modeling -- 13. Assessment and Validation in Quantile Composite-Based Path Modeling -- 14. PLS-Frailty Model for Cancer Survival Analysis Based on Gene Expression Profiles -- 15. Functional Linear Regression Analysis Based on Partial Least Squares and Its Application -- 16. Multiblock and Multigroup PLS Application to Study Cannabis Consumption in Thirteen European Countries -- 17. A Unified Framework to Study the Properties of the PLS Vector of Regression Coefficients -- 18. A New Bootstrap-Based Stopping Criterion in PLS Components Construction -- 19. Extension to the PATHMOX Approach to Detect which Constructs Differentiate Segments and to Test Factor Invariance: Application to Mental Health Data -- 20. Multi-Group Invariance Testing: An Illustrative Comparison of PLS Permutation and Covariance-Based SEM Invariance Analysis -- 21. Brand Nostalgia and Consumers' Relationships to Luxury Brands: A Continuous and Categorical Moderated Mediation Approach -- 22. A Partial Least Squares Algorithm Handling Ordinal Variables.
520 $a This volume presents state of the art theories, new developments, and important applications of Partial Least Square (PLS) methods. The text begins with the invited communications of current leaders in the field who cover the history of PLS, an overview of methodological issues, and recent advances in regression and multi-block approaches. The rest of the volume comprises selected, reviewed contributions from the 8th International Conference on Partial Least Squares and Related Methods held in Paris, France, on 26-28 May, 2014. They are organized in four coherent sections: 1) new developments in genomics and brain imaging, 2) new and alternative methods for multi-table and path analysis, 3) advances in partial least square regression (PLSR), and 4) partial least square path modeling (PLS-PM) breakthroughs and applications. PLS methods are very versatile methods that are now used in areas as diverse as engineering, life science, sociology, psychology, brain imaging, genomics, and business among both academics and practitioners. The selected chapters here highlight this diversity with applied examples as well as the most recent advances. Integrates theoretical and methodological advances from recognized leaders in the field, including the conference's invited speakers Important applications in domains such as genomics, brain imaging, sensory analysis, marketing, psychometrics and information systems Covers PLS regression, PLS path modeling and developments that go beyond PLS specific methods, extending to other component-based and multi-block or multi-way methods.
650 0 $a Least squares $3 168711
650 1 4 $a Statistics. $3 145349
650 2 4 $a Statistical Theory and Methods. $3 464135
650 2 4 $a Mathematical Models of Cognitive Processes and Neural Networks. $3 590938
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 464764
700 1 $a Abdi, Herve. $3 673064
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
830 0 $a Springer proceedings in mathematics & statistics ; $v v.70. $3 589270
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-40643-5
950 $a Mathematics and Statistics (Springer-11649)