coreMDS function

coreMDS

coreMDS performs metric multidimensional scaling (MDS). UTF-8

coreMDS(DATA, masses = NULL, decomp.approach = 'svd', k = 0)

Arguments

• DATA: original data to decompose and analyze via the singular value decomposition.
• masses: a vector or diagonal matrix with masses for the rows (observations). If NULL, one is created.
• decomp.approach: string. A switch for different decompositions (typically for speed). See pickSVD.
• k: number of components to return (this is not a rotation, just an a priori selection of how much data should be returned).

Details

epMDS should not be used directly unless you plan on writing extensions to ExPosition. See epMDS

Returns

Returns a large list of items which are also returned in epMDS.

All items with a letter followed by an i are for the I rows of a DATA matrix. All items with a letter followed by an j are for the J rows of a DATA matrix.

• fi: factor scores for the row items.

• di: square distances of the row items.

• ci: contributions (to the variance) of the row items.

• ri: cosines of the row items.

• masses: a column-vector or diagonal matrix of masses (for the rows)

• t: the percent of explained variance per component (tau).

• eigs: the eigenvalues from the decomposition.

• pdq: the set of left singular vectors (pdq$p) for the rows, singular values (pdq$Dv and pdq$Dd), and the set of right singular vectors (pdq$q) for the columns.

• X: the final matrix that was decomposed (includes scaling, centering, masses, etc...).

References

Abdi, H. (2007). Metric multidimensional scaling. In N.J. Salkind (Ed.): Encyclopedia of Measurement and Statistics. Thousand Oaks (CA): Sage. pp. 598-605.

O'Toole, A. J., Jiang, F., Abdi, H., and Haxby, J. V. (2005). Partially distributed representations of objects and faces in ventral temporal cortex. Journal of Cognitive Neuroscience, 17(4), 580-590.

Author(s)

Derek Beaton and Hervé Abdi.

See Also

epMDS