Description Usage Arguments Details Value Author(s) References See Also Examples

Compute the discrepancy from the pairwise dissimilarities between objects. The discrepancy is a measure of dispersion of the set of objects.

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`diss` |
A dissimilarity matrix or a |

`weights` |
optional numerical vector containing weights. |

`squared` |
Logical. If |

The discrepancy is an extension of the concept of variance to any kind of objects for which we can compute pairwise dissimilarities.
The discrepancy *s^2* is defined as:

*s^2=(1/(2n^2)) * sum sum d_ij*

*Mathematical ground*:
In the Euclidean case, the sum of squares can be expressed as:

*SS= sum (y_i - y_mean)^2=(1/(2n)) * sum sum (y_i - y_j)^2*

The concept of discrepancy generalizes the equation by allowing to replace the *(y_i - y_j)^2* term with any measure of dissimilarity *d_{ij}*.

The discrepancy.

Matthias Studer (with Gilbert Ritschard for the help page)

Studer, M., G. Ritschard, A. Gabadinho and N. S. M<c3><bc>ller (2011). Discrepancy analysis of state sequences, *Sociological Methods and Research*, Vol. 40(3), 471-510.

Studer, M., G. Ritschard, A. Gabadinho and N. S. M<c3><bc>ller (2010)
Discrepancy analysis of complex objects using dissimilarities.
In F. Guillet, G. Ritschard, D. A. Zighed and H. Briand (Eds.),
*Advances in Knowledge Discovery and Management*,
Studies in Computational Intelligence, Volume 292, pp. 3-19. Berlin: Springer.

Studer, M., G. Ritschard, A. Gabadinho and N. S. M<c3><bc>ller (2009)
Analyse de dissimilarit<c3><a9>s par arbre d'induction. In EGC 2009,
*Revue des Nouvelles Technologies de l'Information*, Vol. E-15, pp. 7-18.

Anderson, M. J. (2001) A new method for non-parametric multivariate analysis of variance.
*Austral Ecology* **26**, 32-46.

Batagelj, V. (1988) Generalized ward and related clustering problems. In H. Bock (Ed.),
*Classification and related methods of data analysis*, Amsterdam: North-Holland, pp. 67-74.

`dissassoc`

to test association between objects represented by their dissimilarities and a covariate.

`disstree`

for an induction tree analyse of objects characterized by a dissimilarity matrix.

`disscenter`

to compute the distance of each object to its group center from pairwise dissimilarities.

`dissmfacw`

to perform multi-factor analysis of variance from pairwise dissimilarities.

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