Add to ORKGThis work is on the development of an observation reduction technique based on the principal component scores, or loadings, intended for the classification of data
Multivariate analysis deals with the statistical analysis of observations where there are multiple r...
This book offers a concise and well-organized introduction to multivariate statistical analysis meth...
Principal Components are probably the best known and most widely used of all multivariate analysis t...
This work is on the development of an observation reduction technique based on the principal compone...
This thesis introduces new algorithms for analysis and classification of multivariate data. Statisti...
A practical guide for multivariate statistical techniques-- now updated and revised In recent years...
Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a c...
Master's thesis in Computer scienceCollected data from the sensors monitoring the environment in oil...
The proceedings contain 49 papers. The topics discussed include: principal component analysis for ca...
The information age has resulted in masses of data in every field. Techniques to analyse this data a...
Describes the advances in computation and data storage that led to the introduction of many statisti...
We propose a computer intensive method for linear dimension reduction which minimizes the classifica...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Dimensionality reduction is the process of reducing the number of features in a data set. In a class...
In this paper, control variates are proposed to speed up Monte Carlo Simulations to estimate expecte...
Multivariate analysis deals with the statistical analysis of observations where there are multiple r...
This book offers a concise and well-organized introduction to multivariate statistical analysis meth...
Principal Components are probably the best known and most widely used of all multivariate analysis t...
This work is on the development of an observation reduction technique based on the principal compone...
This thesis introduces new algorithms for analysis and classification of multivariate data. Statisti...
A practical guide for multivariate statistical techniques-- now updated and revised In recent years...
Statistical Methods of Discrimination and Classification: Advances in Theory and Applications is a c...
Master's thesis in Computer scienceCollected data from the sensors monitoring the environment in oil...
The proceedings contain 49 papers. The topics discussed include: principal component analysis for ca...
The information age has resulted in masses of data in every field. Techniques to analyse this data a...
Describes the advances in computation and data storage that led to the introduction of many statisti...
We propose a computer intensive method for linear dimension reduction which minimizes the classifica...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Dimensionality reduction is the process of reducing the number of features in a data set. In a class...
In this paper, control variates are proposed to speed up Monte Carlo Simulations to estimate expecte...
Multivariate analysis deals with the statistical analysis of observations where there are multiple r...
This book offers a concise and well-organized introduction to multivariate statistical analysis meth...
Principal Components are probably the best known and most widely used of all multivariate analysis t...