find.best {phyclust} | R Documentation |
Find the Best Solution of phyclust
Description
Based on input initialization procedures and methods, this function tries to find the best solution in terms of the highest log-likelihood value.
Usage
find.best(X, K, EMC = .EMC, manual.id = NULL, byrow = TRUE,
init.procedure = .init.procedure, init.method = .init.method,
file.tmp = NULL, visible = FALSE, save.all = FALSE)
Arguments
X |
nid/sid matrix with |
K |
number of clusters. |
EMC |
EM control. |
manual.id |
manually input class ids. |
byrow |
advanced option for |
init.procedure |
customized initialization procedures. |
init.method |
customized initialization methods. |
file.tmp |
a file for saving temporary results. |
visible |
TRUE for reporting iterations. |
save.all |
TRUE for saving all results. |
Details
X
should be a numerical matrix containing sequence data that
can be transfered by code2nid
or code2sid
.
Note: gaps -
are not supported yet, drop them from data.
EMC
contains all options used for EM algorithms.
manual.id
manually input class ids as an initialization only for
the initialization method, 'manualMu'.
byrow
used in bootstraps to avoid transposing matrix 'X'. If
FALSE, then the 'X' should be have the dimension L\times K
.
init.procedure
and init.method
are methods for searching
the best result. This function will try all combinations of these two
options.
file.tmp
is used to save temporary results due to long computing.
If NULL
, there will no saving in each combinations.
Value
An list with class phyclust
will be returned containing
several elements, see phyclust
for detail.
ToDo(s)
implement codes for gaps
-
.
Author(s)
Wei-Chen Chen wccsnow@gmail.com
References
Phylogenetic Clustering Website: https://snoweye.github.io/phyclust/
See Also
Examples
## Not run:
library(phyclust, quiet = TRUE)
set.seed(1234)
EMC.1 <- .EMControl(exhaust.iter = 1, short.iter = 5, EM.iter = 5)
(ret.1 <- find.best(seq.data.toy$org, 2, EMC = EMC.1))
## End(Not run)