tmklm {dBlockmodeling} | R Documentation |
This function runs two-mode K-means for an RO x CO network matrix.
tmklm(A, RC, CC, TLIMIT)
A |
An RO x CO two-mode network matrix. |
RC |
The number of clusters for row objects (1 < RC < RO). |
CC |
The number of clusters for column objects (1 < CC < CO). |
TLIMIT |
A desired time limit. |
The function returns the following:
vaf
- the variance-accounted-for;
RP
- an RO-dimensional vector of row cluser assignements;
RC
- an RC-dimensional vector of column cluser assignements;
restarts
- the number of restarts within the time limit.
Michael Brusco
Brusco, M. J., Doreian, P., & Steinley, D. (2019). Deterministic blockmodeling of signed and two-mode networks: a tutorial with psychological examples. British Journal of Mathematical and Statistical Psychology.
Baier, D., Gaul, W., & Schader, M. (1997). Two-mode overlapping clustering with applications in simultaneous benefit segmentation and market structuring. In R. Klar & O. Opitz (Eds), Classification and knowledge organization (pp. 557-566), Heidelberg: Springer.
Brusco, M., & Doreian, P. (2015). A real-coded genetic algorithm for two-mode KL-means partitioning with application to homogeneity blockmodeling. Social Networks, 41, 26-35. http://dx.doi.org/10.1016/j.socnet.2014.11.007
# Load the Turning Point Project network (Brusco & Doreian, 2015) data. data("nyt") # Run two-mode K-means procedure. res <- tmklm(nyt,RC = 9,CC = 5,TLIMIT = 1) # See the results. res