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G03 (Mv)
Multivariate Methods

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G03 (Mv) Chapter Introduction – A description of the Chapter and an overview of the algorithms available.

Mark of

g03aaf 14 nagf_mv_prin_comp
Performs principal component analysis
g03acf 14 nagf_mv_canon_var
Performs canonical variate analysis
g03adf 14 nagf_mv_canon_corr
Performs canonical correlation analysis
g03baf 15 nagf_mv_rot_orthomax
Computes orthogonal rotations for loading matrix, generalized orthomax criterion
g03bcf 15 nagf_mv_rot_procrustes
Computes Procrustes rotations
g03bdf 22 nagf_mv_rot_promax
ProMax rotations
g03caf 15 nagf_mv_factor
Computes maximum likelihood estimates of the parameters of a factor analysis model, factor loadings, communalities and residual correlations
g03ccf 15 nagf_mv_factor_score
Computes factor score coefficients (for use after g03caf)
g03daf 15 nagf_mv_discrim
Computes test statistic for equality of within-group covariance matrices and matrices for discriminant analysis
g03dbf 15 nagf_mv_discrim_mahal
Computes Mahalanobis squared distances for group or pooled variance-covariance matrices (for use after g03daf)
g03dcf 15 nagf_mv_discrim_group
Allocates observations to groups according to selected rules (for use after g03daf)
g03eaf 16 nagf_mv_distance_mat
Computes distance matrix
g03ecf 16 nagf_mv_cluster_hier
Hierarchical cluster analysis
g03eff 16 nagf_mv_cluster_kmeans
K-means cluster analysis
g03ehf 16 nagf_mv_cluster_hier_dendrogram
Constructs dendrogram (for use after g03ecf)
g03ejf 16 nagf_mv_cluster_hier_indicator
Computes cluster indicator variable (for use after g03ecf)
g03faf 17 nagf_mv_multidimscal_metric
Performs principal coordinate analysis, classical metric scaling
g03fcf 17 nagf_mv_multidimscal_ordinal
Performs non-metric (ordinal) multidimensional scaling
g03gaf 24 nagf_mv_gaussian_mixture
Fits a Gaussian mixture model
g03zaf 15 nagf_mv_z_scores
Produces standardized values (z-scores) for a data matrix