Several standard multivariate methods are provided by Genstat directives. These include methods that analyse data in the form of units-by-variates, and methods that use a similarity or distance matrix.
The following directives carry out standard multivariate analyses:
CVA |
canonical variates analysis |
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FCA |
factor analysis |
MDS |
non-metric multidimensional scaling |
PCP |
principal components analysis |
PCO |
principal coordinates analysis |
ROTATE |
Procrustes rotation |
Other directives and procedures are available to process results from multivariate analyses:
ADDPOINTS |
adds points for new objects to a PCO |
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CVAPLOT |
plots the mean and unit scores from a canonical variates analysis |
CVASCORES |
calculates scores for individual units in canonical variates analysis |
CVATRELLIS |
displays the distribution of groups over 2 dimensions from a CVA analysis using a trellis of bar or pie charts |
DBIPLOT |
plots a biplot from an analysis by PCP , CVA or PCO |
DMST |
gives a high resolution plot of an ordination with minimum spanning tree |
FACROTATE |
rotates factor loadings from a PCP , CVA or FCA ADDPOINTS |
LRVSCREE |
prints a scree diagram and/or a difference table of latent roots |
PCORELATE |
relates principal coordinates to original data variables |
The following commands carry out hierarchical and non-hierarchical cluster analysis:
CLUSTER |
non-hierarchical clustering from a data matrix |
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FSIMILARITY |
forms a similarity matrix or a between-group similarity matrix from a units-by-variates data matrix |
HREDUCE |
forms a reduced similarity matrix (by groups) |
HCLUSTER |
hierarchical cluster analysis from a similarity matrix |
PCPCLUSTER |
forms groups of units using the densities of their PCP scores |
PTFCLUSTERS |
forms clusters of points from their densities in multi-dimensional space |
Other directives and procedures that process the results from cluster analyses are:
DDENDROGRAM |
draws dendrograms with control over structure and style |
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DCLUSTERLABELS |
labels clusters in a single-page dendrogram plotted by DDENDROGRAM |
HBOOTSTRAP |
performs bootstrap analyses to assess the reliability of clusters from hierarchical cluster analysis |
HCOMPAREGROUPINGS |
compares groupings generated, for example, from cluster analyses |
HDISPLAY |
displays results associated with hierarchical clustering |
HFAMALGAMATIONS |
forms an amalgamations |
HFCLUSTERS |
forms a set of clusters from an amalgamations matrix |
HLIST |
lists a data matrix in abbreviated form |
HPCLUSTERS |
prints a set of clusters |
HSUMMARIZE |
summarizes data variates by clusters |
PTFILLCLUSTERS |
fills holes within clusters of points in multi-dimensional space |
Other multivariate techniques are provided by procedures in the Library:
AMMI |
allows exploratory analysis of genotype × environment interactions |
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BCLASSIFICATION |
constructs a classification tree |
BCDISPLAY |
displays a classification tree |
BCIDENTIFY |
identifies specimens using a classification tree |
BCKEEP |
saves information from a classification tree |
BCVALUES |
forms values for nodes of a classification tree |
BCFOREST |
constructs a random classification forest |
BCFDISPLAY |
displays information about a random classification forest |
BCFIDENTIFY |
identifies specimens using a random classification forest |
BIPLOT |
produces a biplot from a set of variates |
BKEY |
constructs an identification key |
BKDISPLAY |
displays an identification key |
BKIDENTIFY |
identifies specimens using a key |
BKKEEP |
saves information from an identification key |
CANCORRELATION |
does canonical correlation analysis |
CCA |
performs canonical correspondence analysis |
CRBIPLOT |
plots correlation or distance biplots after CCA or RDA |
CRTRIPLOT |
plots ordination biplots or triplots after CCA or RDA |
CINTERACTION |
clusters rows and columns of a two-way interaction table |
CLASSIFY |
obtains a starting classification for non-hierarchical clustering |
CONVEXHULL |
finds the points of a single or a full peel of convex-hulls |
CORANALYSIS |
does correspondence analysis, or reciprocal averaging |
MCORANALYSIS |
does multiple correspondence analysis |
CABIPLOT |
plots results from correspondence analysis or multiple correspondence analysis |
DISCRIMINATE |
performs discriminant analysis |
SDISCRIMINATE |
selects the best set of variates to discriminate between groups |
QDISCRIMINATE |
performs quadratic discrimination between groups i.e. allowing for different variance-covariance matrices |
DPARALLEL |
displays multivariate data using parallel coordinates |
GESTABILITY |
calculates stability coefficients for genotype-by-environment data |
GGEBIPLOT |
plots displays to assess genotype + genotype-by-environment variation |
GENPROCRUSTES |
performs a generalized Procrustes analysis |
IDENTIFY |
identifies an unknown specimen from a defined set of objects |
KNEARESTNEIGHBOURS |
classifies items or predicts their responses by examining their k nearest neighbours |
MANOVA |
performs multivariate analysis of variance and covariance |
MANTEL |
assesses the association between similarity matrices |
MULTMISSING |
estimates missing values for units in a multivariate data set |
MVAOD |
does an analysis of distance of multivariate data |
NORMTEST |
performs tests of univariate and/or multivariate normality |
OPLS |
performs orthogonal partial least squares regression |
PCOPROCRUSTES |
performs a multiple Procrustes analysis |
PLS |
fits a partial least squares regression model |
RDA |
performs redundancy analysis |
RIDGE |
produces ridge regression and principal component regression analyses |
LRIDGE |
does logistic ridge regression |
RLFUNCTIONAL |
fits a linear functional relationship model |
RMULTIVARIATE |
performs multivariate linear regression with accumulated testing of terms |
ROBSSPM |
forms robust estimates of sum-of-squares-and-products matrices |
SAGRAPES |
produces statistics and graphs for checking sensory panel performance |
SKEWSYMMETRY |
provides an analysis of skew-symmetry for an asymmetric matrix |