| find.best {phyclust} | R Documentation |
Based on input initialization procedures and methods, this function tries to find the best solution in terms of the highest log-likelihood value.
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)
X |
nid/sid matrix with N rows/sequences and L columns/sites. |
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. |
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*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.
An list with class phyclust will be returned containing
several elements, see phyclust for detail.
implement codes for gaps -.
Wei-Chen Chen wccsnow@gmail.com
Phylogenetic Clustering Website: http://snoweye.github.io/phyclust/
## 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)