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Data Analysis and Applications 1 : New and Classical Approaches.
"This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models, and techniques, along with appropriate applications. Volume 1 begins with an introductory chapter by Gilbert Saporta, a leading expert in th...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Newark :
John Wiley & Sons, Incorporated,
2019.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mi 4500 | ||
|---|---|---|---|
| 001 | EBOOKCENTRAL_on1089986481 | ||
| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
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| 008 | 190316s2019 nju o 000 0 eng d | ||
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| 019 | |a 1104316702 |a 1104400506 | ||
| 020 | |a 9781119597575 | ||
| 020 | |a 1119597579 | ||
| 020 | |a 9781786303820 | ||
| 020 | |a 1786303825 | ||
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| 035 | |a (OCoLC)1089986481 |z (OCoLC)1104316702 |z (OCoLC)1104400506 | ||
| 050 | 4 | |a QA76.9.Q36 |b .D383 2019 | |
| 082 | 0 | 4 | |a 001.42 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Skiadas, Christos. | |
| 245 | 1 | 0 | |a Data Analysis and Applications 1 : |b New and Classical Approaches. |
| 260 | |a Newark : |b John Wiley & Sons, Incorporated, |c 2019. | ||
| 300 | |a 1 online resource (291 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover; Half-Title Page; Title Page; Copyright Page; Contents; Preface; Introduction: 50 Years of Data Analysis: From Exploratory Data Analysis to Predictive Modeling and Machine Learning; I.1. The revolt against mathematical statistics; I.2. EDA and unsupervised methods for dimension reduction; I.2.1. The time of syntheses; I.2.2. The time of clusterwise methods; I.2.3. Extensions to new types of data; I.2.4. Nonlinear data analysis; I.2.5. The time of sparse methods; I.3. Predictive modeling; I.3.1. Paradigms and paradoxes; I.3.2. From statistical learning theory to empirical validation | |
| 505 | 8 | |a I.3.3. ChallengesI. 4. Conclusion; I.5. References; PART 1: Clustering and Regression; 1. Cluster Validation by Measurement of Clustering Characteristics Relevant to the User; 1.1. Introduction; 1.2. General notation; 1.3. Aspects of cluster validity; 1.3.1. Small within-cluster dissimilarities; 1.3.2. Between-cluster separation; 1.3.3. Representation of objects by centroids; 1.3.4. Representation of dissimilarity structure by clustering; 1.3.5. Small within-cluster gaps; 1.3.6. Density modes and valleys; 1.3.7. Uniform within-cluster density; 1.3.8. Entropy; 1.3.9. Parsimony | |
| 505 | 8 | |a 1.3.10. Similarity to homogeneous distributional shapes1.3.11. Stability; 1.3.12. Further Aspects; 1.4. Aggregation of indexes; 1.5. Random clusterings for calibrating indexes; 1.5.1. Stupid K-centroids clustering; 1.5.2. Stupid nearest neighbors clustering; 1.5.3. Calibration; 1.6. Examples; 1.6.1. Artificial data set; 1.6.2. Tetragonula bees data; 1.7. Conclusion; 1.8. Acknowledgment; 1.9. References; 2. Histogram-Based Clustering of Sensor Network Data; 2.1. Introduction; 2.2. Time series data stream clustering; 2.2.1. Local clustering of histogram data | |
| 505 | 8 | |a 2.2.2. Online proximity matrix updating2.2.3. Off-line partitioning through the dynamic clustering algorithm for dissimilarity tables; 2.3. Results on real data; 2.4. Conclusions; 2.5. References; 3. The Flexible Beta Regression Model; 3.1. Introduction; 3.2. The FB distribution; 3.2.1. The beta distribution; 3.2.2. The FB distribution; 3.2.3. Reparameterization of the FB; 3.3. The FB regression model; 3.4. Bayesian inference; 3.5. Illustrative application; 3.6. Conclusion; 3.7. References; 4. S-weighted Instrumental Variables; 4.1. Summarizing the previous relevant results | |
| 505 | 8 | |a 4.2. The notations, framework, conditions and main tool4.3. S-weighted estimator and its consistency; 4.4. S-weighted instrumental variables and their consistency; 4.5. Patterns of results of simulations; 4.5.1. Generating the data; 4.5.2. Reporting the results; 4.6. Acknowledgment; 4.7. References; PART 2: Models and Modeling; 5. Grouping Property and Decomposition of Explained Variance in Linear Regression; 5.1. Introduction; 5.2. CAR scores; 5.2.1. Definition and estimators; 5.2.2. Historical criticism of the CAR scores; 5.3. Variance decomposition methods and SVD | |
| 500 | |a 5.4. Grouping property of variance decomposition methods | ||
| 520 | |a "This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models, and techniques, along with appropriate applications. Volume 1 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into three parts: Part 1 presents clustering and regression cases; Part 2 examines grouping and decomposition, GARCH and threshold models, structural equations, and SME modeling; and Part 3 presents symbolic data analysis, time series and multiple choice models, modeling in demography, and data mining."-- |c Provided by publisher. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Quantitative research. | |
| 650 | 4 | |a Forecasting. | |
| 650 | 4 | |a Regression Analysis. | |
| 650 | 4 | |a Data Mining. | |
| 650 | 4 | |a Social Science |x Future Studies. | |
| 650 | 4 | |a Mathematics |x Probability & Statistics |x Regression Analysis. | |
| 650 | 4 | |a Computers |x Data Science |x Data Analytics. | |
| 650 | 6 | |a Recherche quantitative. | |
| 650 | 7 | |a Quantitative research |2 fast | |
| 700 | 1 | |a Bozeman, James R. | |
| 776 | 0 | 8 | |i Print version: |a Skiadas, Christos. |t Data Analysis and Applications 1 : New and Classical Approaches. |d Newark : John Wiley & Sons, Incorporated, ©2019 |z 9781786303820 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5724037 |z Texto completo |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL5724037 | ||
| 994 | |a 92 |b IZTAP | ||