Function |
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_rot_orthomax Orthogonal rotations for loading matrix |
g03bcc | 5 | nag_mv_rot_procrustes Procrustes rotations |
g03bdc | 9 | nag_mv_rot_promax ProMax rotations |
g03cac | 5 | nag_mv_factor Maximum likelihood estimates of parameters |
g03ccc | 5 | nag_mv_factor_score Factor score coefficients, following g03cac |
g03dac | 5 | nag_mv_discrim Test for equality of within-group covariance matrices |
g03dbc | 5 | nag_mv_discrim_mahal 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 |
g03ebc | 29.2 | nag_mv_distance_mat_2 Compute distance (dissimilarity) matrix for two input matrices |
g03ecc | 5 | nag_mv_cluster_hier Hierarchical cluster analysis |
g03efc | 5 | nag_mv_cluster_kmeans -means |
g03ehc | 5 | nag_mv_cluster_hier_dendrogram Construct dendogram following g03ecc |
g03ejc | 5 | nag_mv_cluster_hier_indicator Construct clusters following g03ecc |
g03fac | 5 | nag_mv_multidimscal_metric Principal coordinate analysis |
g03fcc | 5 | nag_mv_multidimscal_ordinal Multidimensional scaling |
g03gac | 24 | nag_mv_gaussian_mixture Fits a Gaussian mixture model |
g03gbc | 29 | nag_mv_gaussian_mixture_ld Fits a Gaussian mixture model with results stored in submatrices |
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 |