tmklmed {dBlockmodeling} | R Documentation |
This function runs two-mode KL-medians for an RO x CO two-mode binary network matrix.
tmklmed(A, RC, CC, TLIMIT)
A |
An RO x CO two-mode binary 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:
objval
- total number of inconsistencies;
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.
Doreian, P., Batagelj, V., & Ferligoj, A. (2004). Generalized blockmodeling of two-mode network data. Social Networks, 26, 29-53. doi:10.1016/j.socnet.2004.01.002
Brusco, M., Stolze, H. J., Hoffman, M., Steinley, D., & Doreian, P. (2018). Deterministic blockmodeling of two-mode binary network data using two-mode KL-median partitioning. Journal of Social Structure, 19, 1-21. Retrieved from: https://www.exeley.com/exeley/journals/journal_of_social_structure/19/1/pdf/10.21307_joss-2018-007.pdf
# Load the Turning Point Project network (Brusco & Doreian, 2015) data. data("nyt") # Run the two-mode blockmodeling heuristic procedure. res <- tmklmed(nyt, RC = 9, CC = 5, TLIMIT = 1) # See the results. res