NAG Fortran Library

G03 – Multivariate Methods

G03 Chapter Introduction

Routine
Name
Mark of
Introduction

Purpose
G03AAF Example Text Example Data 14 Performs principal component analysis
G03ACF Example Text Example Data 14 Performs canonical variate analysis
G03ADF Example Text Example Data 14 Performs canonical correlation analysis
G03BAF Example Text Example Data 15 Computes orthogonal rotations for loading matrix, generalized orthomax criterion
G03BCF Example Text Example Data 15 Computes Procrustes rotations
G03CAF Example Text Example Data 15 Computes maximum likelihood estimates of the parameters of a factor analysis model, factor loadings, communalities and residual correlations
G03CCF Example Text Example Data 15 Computes factor score coefficients (for use after G03CAF)
G03DAF Example Text Example Data 15 Computes test statistic for equality of within-group covariance matrices and matrices for discriminant analysis
G03DBF Example Text Example Data 15 Computes Mahalanobis squared distances for group or pooled variance-covariance matrices (for use after G03DAF)
G03DCF Example Text Example Data 15 Allocates observations to groups according to selected rules (for use after G03DAF)
G03EAF Example Text Example Data 16 Computes distance matrix
G03ECF Example Text Example Data 16 Hierarchical cluster analysis
G03EFF Example Text Example Data 16 K-means cluster analysis
G03EHF Example Text Example Data 16 Constructs dendrogram (for use after G03ECF)
G03EJF Example Text Example Data 16 Computes cluster indicator variable (for use after G03ECF)
G03FAF Example Text Example Data 17 Performs principal co-ordinate analysis, classical metric scaling
G03FCF Example Text Example Data 17 Performs non-metric (ordinal) multidimensional scaling
G03ZAF Example Text Example Data 15 Produces standardized values (z-scores) for a data matrix

Table of Contents
© The Numerical Algorithms Group Ltd, Oxford UK. 2002