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When specifying a mixture model (which is done when using Create > Segments) the following options are available for specifying the shape of the mixing distribution.
- Finite Assumes that there is no variation within each class. This is the default.
- Multivariate Normal – Spherical Forces the classes to be “spherical” (i.e., with equal variances for every variable).
- Multivariate Normal – Diagonal Estimates separate variances for each variable (i.e., in the case of Number and Number - Multi questions, this is equivalent to transforming the data to z-scores).
- Multivariate Normal – Block Diagonal Permits correlation between levels of the same attribute, but not between attributes.
- Multivariate Normal – Full Covariance Permits correlations between all attributes and attribute levels.
- These assumptions are ordered from most restrict to least restrictive.
- Pool variance Constrains the variance and covariance assumptions to be common across classes. For example, if Multivariate Normal – Spherical and Pool variance are both selected, a single variance parameter is employed for the entire model.
Further reading: Market Segmentation Software