"Introduction to High-Dimensional Statistics, Second Edition preserves the philosophy of the first edition: to be a concise guide for students and researchers discovering the area and interested in the mathematics involved. The main concepts and ideas are presented in simple set…
1. Introduction. 2. Regionalized Compositions. 3. Spatial Covariance Structure. 4. Concepts of Null Correlation. 5. Cokriging. 6. Practical Aspects of Compositional Data Analysis. 7. Application to Real Data. Summary andProspects. References. Index.
1. Introduction. 2. Regionalized Compositions. 3. Spatial Covariance Structure. 4. Concepts of Null Correlation. 5. Cokriging. 6. Practical Aspects of Compositional Data Analysis. 7. Application to Real Data. Summary and Prospects. References. Index.
1. Introduction. 2. Regionalized Compositions. 3. Spatial Covariance Structure. 4. Concepts of Null Correlation. 5. Cokriging. 6. Practical Aspects of Compositional Data Analysis. 7. Application to Real Data. Summary and Prospects. References. Index.
This text in multivariable calculus fosters comprehension through meaningful explanations. Written with students in mathematics, the physical sciences, and engineering in mind, it extends concepts from single variable calculus such as derivative, integral, and important theorems…
This text in multivariable calculus fosters comprehension through meaningful explanations. Written with students in mathematics, the physical sciences, and engineering in mind, it extends concepts from single variable calculus such as derivative, integral, and important theorems…
This text in multivariable calculus fosters comprehension through meaningful explanations. Written with students in mathematics, the physical sciences, and engineering in mind, it extends concepts from single variable calculus such as derivative, integral, and important theorems…
