Description Usage Arguments Value Author(s) References See Also Examples
Fits the Mallows mixture model to total rankings, using EM algorithm, for clustering permutations.
1 2 3 4 5 6 7 | Mallows(datas, G, weights = NULL, iter = 100, iterin = iter,
tol = 0.001, logsumexp.trick = TRUE, seed = 47631439,
key = c("copelandMallows", "bruteMallows", "bordaMallows", "kernelMallows",
"kernelMallows_Exh", "kernelGaussian", "copelandMallows_Eqlam",
"bruteMallows_Eqlam", "bordaMallows_Eqlam", "kernelMallows_Eqlam",
"kernelMallows_Exh_Eqlam", "kernelGaussian_Eqlam"), exhkey = "_Exh",
eqlamkey = "_Eqlam")
|
datas |
Matrix of dimension |
G |
Number of modes, 2 or greater. |
weights |
Numeric vector of length |
iter |
Maximum number of iterations for EM algorithm. |
iterin |
Maximum number of iterations for alternate optimization between centers and lambda. Effective only when performing kernel Mallows with exhaustive optimization. |
tol |
Stopping precision. |
logsumexp.trick |
Logical. Whether or not to use log-sum-exp trick to compute log-likelihood. |
seed |
Seed index for reproducible results when optimization is performed. Set to NULL to disable the action. |
key |
A character string defining the type of Mallows mixture model to perform:
|
exhkey |
DO NOT CHANGE. A character string. If it greps successfully in " |
eqlamkey |
DO NOT CHANGE. A character string. If it greps successfully in " |
List.
key |
Character string indicating the type of Mallows mixture model performed |
R |
List of length " |
p |
Numeric vector of length " |
lambda |
Numeric vector of length " |
datas |
A copy of " |
min.like |
Numeric vector of length " |
Yunlong Jiao
Thomas Brendan Murphy, Donal Martin. "Mixtures of distance-based models for ranking data." Computational Statistics & Data Analysis, vol. 41, no. 3, pp. 645-655, 2003. DOI:10.1016/S0167-9473(02)00165-2
Yunlong Jiao, Jean-Philippe Vert. "The Kendall and Mallows Kernels for Permutations." IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 40, no. 7, pp. 1755-1769, 2018. DOI:10.1109/TPAMI.2017.2719680
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