NAG C Library

g03 – Multivariate Methods

g03 Chapter Introduction

Routine
Name
Mark of
Introduction

Purpose
g03aac 5 nag_mv_prin_comp
Principal component analysis
g03acc 5 nag_mv_canon_var
Canonical variate analysis
g03adc 5 nag_mv_canon_corr
Canonical correlation analysis
g03bac 5 nag_mv_orthomax
Orthogonal rotations for loading matrix
g03bcc 5 nag_mv_procustes
Procrustes rotations
g03cac 5 nag_mv_factor
Maximum likelihood estimates of parameters
g03ccc 5 nag_mv_fac_score
Factor score coefficients, following g03cac
g03dac 5 nag_mv_discrim
Test for equality of within-group covariance matrices
g03dbc 5 nag_mv_discrim_mahaldist
Mahalanobis squared distances, following g03dac
g03dcc 5 nag_mv_discrim_group
Allocates observations to groups, following g03dac
g03eac 5 nag_mv_distance_mat
Compute distance (dissimilarity) matrix
g03ecc 5 nag_mv_hierar_cluster_analysis
Hierarchical cluster analysis
g03efc 5 nag_mv_kmeans_cluster_analysis
K-means
g03ehc 5 nag_mv_dendrogram
Construct dendogram following g03ecc
g03ejc 5 nag_mv_cluster_indicator
Construct clusters following g03ecc
g03fac 5 nag_mv_prin_coord_analysis
Principal co-ordinate analysis
g03fcc 5 nag_mv_ordinal_multidimscale
Multidimensional scaling
g03xzc 5 nag_mv_dend_free
Frees memory allocated to the dendrogram array in g03ehc
g03zac 5 nag_mv_z_scores
Standardize values of a data matrix

NAG C Library
© The Numerical Algorithms Group Ltd, Oxford UK. 2002