In statistics, **Procrustes analysis** is a form of statistical shape analysis used to analyse the distribution of a set of shapes. The name Procrustes refers to a bandit from Greek mythology who made his victims fit his bed either by stretching their limbs or cutting them off.

To compare the shape of two or more objects, the objects must be first optimally "superimposed". **Procrustes superimposition** (PS) is performed by optimally translating, rotating and uniformly scaling the objects. In other words, both the placement in space and the size of the objects are freely adjusted. The aim is to obtain a similar placement and size, by minimizing a measure of shape difference called the Procrustes distance between the objects. This is sometimes called **full**, as opposed to **partial** PS, in which scaling is not performed (i.e. the size of the objects is preserved). Notice that, after full PS, the objects will exactly coincide if their shape is identical. For instance, with full PS two spheres with different radius will always coincide, because they have exactly the same shape. Conversely, with partial PS they will never coincide. This implies that, by the strict definition of the term *shape* in geometry, shape analysis should be performed using full PS. A statistical analysis based on partial PS is not a pure shape analysis as it is not only sensitive to shape differences, but also to size differences. Both full and partial PS will never manage to perfectly match two objects with different shape, such as a cube and a sphere, or a right hand and a left hand.

In some cases, both full and partial PS may also include reflection. Reflection allows, for instance, a successful (possibly perfect) superimposition of a right hand to a left hand. Thus, partial PS with reflection enabled preserves size but allows translation, rotation and reflection, while full PS with reflection enabled allows translation, rotation, scaling and reflection.

In mathematics:

- an orthogonal Procrustes problem is a method which can be used to find out the optimal
*rotation and/or reflection*(i.e., the optimal orthogonal linear transformation) for the PS of an object with respect to another. - a constrained orthogonal Procrustes problem, subject to det(
*R*) = 1 (where*R*is a rotation matrix), is a method which can be used to determine the optimal*rotation*for the PS of an object with respect to another (reflection is not allowed). In some contexts, this method is called the Kabsch algorithm.

Optimal translation and scaling are determined with much simpler operations (see below).

When a shape is compared to another, or a set of shapes is compared to an arbitrarily selected reference shape, Procrustes analysis is sometimes further qualified as **classical** or **ordinary**, as opposed to **Generalized** Procrustes analysis (GPA), which compares three or more shapes to an optimally determined "mean shape".

Read more about Procrustes Analysis: Ordinary Procrustes Analysis, Generalized Procrustes Analysis (GPA), Variations, Examples, See Also, External Links

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