Introduction to Multivariate Statistical Analysis Vol II

Introduction to Multivariate Statistical Analysis Vol II

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Product Specifications

Publisher Vinra Publication All Engineering Mathematics books by Vinra Publication
Author: Vinra Publication
Number of Pages 265
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Introduction to Multivariate Statistical Analysis Vol II - Page 1 Introduction to Multivariate Statistical Analysis Vol II - Page 2 Introduction to Multivariate Statistical Analysis Vol II - Page 3 Introduction to Multivariate Statistical Analysis Vol II - Page 4 Introduction to Multivariate Statistical Analysis Vol II - Page 5

" Introduction to Multivariate Statistical Analysis Vol II by Vinra Publication


Book Summary:

Encyclopedia of Chemometrics Mathematics and Statistics in Chemistry provides an introduction to multivariate statistical analysis. Multivariate Statistical Analysis covers the mathematical theory of multivariate statistical analysis. Multivariate statistical analysis is an invaluable text for students and a resource for professionals wishing to acquire a basic knowledge of multivariate statistical analysis. This volume contains nine chapters.

The audience of the Book :
This book is Useful for Chemical Engineering and Biochemical Engineering students.
 
Table of Content:

1. Multivariate Statistical Analyses Demonstrate Unique
Host Immune Responses To Single And Dual Lentiviral Infection.

2. Semi-Parametric Modeling of Excesses Above High
Multivariate Thresholds with Censored Data.
 

3. Testing the Equality of Mean Vectors for Paired Doubly
Multivariate Observations in Blocked Compound Symmetric
Covariance Matrix Setup.

4. Generalized Multivariate Birnbaum–Saunders
Distributions and Related Inferential Issues.

5. Tests for Multivariate Analysis of Variance in High
Dimension Under Non-Normality.

6. Testing Rating Scale Unidimensionality Using the Principal
Component Analysis (PCA)/T-Test Protocol With the Rasch
Model: The Primacy of Theory Over Statistics.

7. A Test for Multivariate Skew-Normality Based on its
Canonical Form.

8. An Analysis of Longitudinal Data With Nonignorable
Dropout Using the Truncated Multivariate Normal
Distribution.

9. The Statistical Analysis of Interval-Censored Failure
Time Data with Applications.