# Applied Multivariate Statistical Analysis

@inproceedings{Hrdle2003AppliedMS, title={Applied Multivariate Statistical Analysis}, author={Wolfgang Karl H{\"a}rdle and L{\'e}opold Simar}, year={2003} }

I Descriptive Techniques: Comparison of Batches.- II Multivariate Random Variables: A Short Excursion into Matrix Algebra.- Moving to Higher Dimensions.- Multivariate Distributions.- Theory of the Multinormal.- Theory of Estimation.- Hypothesis Testing.- III Multivariate Techniques: Regression Models.- Variable Selection.- Decomposition of Data Matrices by Factors.- Principal Components Analysis.- Factor Analysis.- Cluster Analysis.- Discriminant Analysis.- Correspondence Analysis.- Canonical…

## 854 Citations

Orthonormal Canonical Correlation Analysis

- Computer ScienceOpen Statistics
- 2021

The orthonormal approximation of data matrices which corresponds to using singular value decomposition in the canonical correlations is presented, which can be helpful in managerial estimations and decision making.

Performance of Some Factor Analysis Techniques

- Economics
- 2020

This paper is a study on three multivariate data sets using some factor analysis techniques in the literature. The techniques are: the principal factor method (PFM), maximum likelihood factor…

Application of the Model of Principal Components Analysis on Romanian Insurance Market

- Computer Science
- 2008

PCA is a linear dimensionality reduction technique, which identifies orthogonal directions of maximum variance in the original data, and projects the data into a lower-dimensionality space formed of a sub-set of the highest-variance components.

Seeking relevant information from a statistical model

- Mathematics, Computer Science
- 2016

A general variable selection procedure is introduced that can be applied to several parametric multivariate problems, including principal components and regression, among others, to allow the identification of a small subset of the original variables that can ‘better explain’ the model through nonparametric relationships.

Methods of Representation for Kernel Canonical Correlation Analysis

- Mathematics, Computer Science
- 2012

This paper constructs nonlinear canonical correlation analysis in reproducing kernel Hilbert spaces and presents methods to solve this problem and compares the results obtained by classical and kernel canonical correlationAnalysis.

Multivariate Small Area Estimation of Multidimensional Latent Economic Well‐being Indicators

- Economics, MathematicsInternational Statistical Review
- 2020

Factor analysis models are used in data dimensionality reduction problems where the variability among observed variables can be described through a smaller number of unobserved latent variables. This…

Multivariate reduced rank regression in non-Gaussian contexts, using copulas

- MathematicsComput. Stat. Data Anal.
- 2008

Applied Quantitative Finance

- Economics
- 2002

Value at Risk.- Modeling Dependencies with Copulae.- Quantification of Spread Risk by Means of Historical Simulation.- A Copula-Based Model of the Term Structure of CDO Tranches.- VaR in High…

LOCALLY STATIONARY FACTOR MODELS: IDENTIFICATION AND NONPARAMETRIC ESTIMATION

- Mathematics, EconomicsEconometric Theory
- 2011

In this paper we propose a new approximate factor model for large cross-section and time dimensions. Factor loadings are assumed to be smooth functions of time, which allows considering the model as…

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