gravity: Gravity dissimilarities

In smacof: Multidimensional Scaling

Gravity dissimilarities

Description

Computes the dissimilarities using a gravity model based on co-occurrences.

Usage

gravity(X, lambda = 1)

Arguments

X	numeric matrix
lambda	tuning parameter

Details

The first step in this function is to compute the co-occurences. Based on the binarized data matrix Y we compute Y'Y which leads to the co-occurence matrix. We then use the gravity model to compute the gravity dissimilarities. In order to give more (or less) structure to the MDS solution, the tuning parameter (which defines a power transformation) can be increased (or decreased). In addition, a weight matrix is created that sets cells with no co-occurences to 0. The corresponding weight matrix for blanking out these cells is established automatically in mds().

Value

gravdiss	Gravity dissimilarities
weightmat	Weight matrix for subsequent smacof computation
co.occ	Matrix with co-occurences

Author(s)

Patrick Mair

References

Mair, P., Rusch, T. & Hornik, K. (2014). The Grand Old Party - A party of values? SpringerPlus, 3(697), https://springerplus.springeropen.com/articles/10.1186/2193-1801-3-697

See Also

mds

Examples

data(GOPdtm)
gravD <- gravity(GOPdtm, lambda = 2)
res <- mds(gravD$gravdiss)  
res$weightmat  ## NA's were blanked out when fitting the model
plot(res)

smacof documentation built on Oct. 10, 2024, 5:09 p.m.