PSTf-class {PST} | R Documentation |
Flat representation of a probabilistic suffix tree
Description
The class "PSTf"
is the flat representation of a probabilistic suffix tree (PST) storing a variable length Markov chain model. The flat representation is a list where each element corresponds to a given depth. It is the prefered representation and is used by all functions for model fitting and sequence analysis with PST. The nested representation "PSTr"
is used only for printing and plotting PSTs.
Objects from the Class
Objects of class "PSTf"
are returned by the pstree
, prune
and tune
function.
Slots
.Data
:Object of class
"list"
, a list where each element corresponds to one level of the tree and is itself a list of nodes, i.e., objects of class"PSTr"
.data
:Object of class
"stslist"
. The learning sample to which the PST is fitted, i.e., a sequence object created with theseqdef
function.cdata
:Object of class
"stslist"
alphabet
:Object of class
"character"
. Alphabet on which the sequences, and the PST are built.labels
:Object of class
"character"
containing the long state labels.cpal
:Object of class
"character"
. Color palette used to represent each state of the alphabet.segmented
:Object of class
"logical"
indicating whether the tree is segmented. Seepstree
.group
:Object of class
"factor"
containing the group membership for each sequence indata
.call
:Object of class
"call"
.logLik
:Object of class
"numeric"
, containing the log-likelihood of the VLMC model represented by the PST.
Extends
Class "list"
, from data part.
Class "vector"
, by class "list", distance 2.
Methods
- cmine
signature(object = "PSTf")
: context mining, seecmine,PSTf-method
.- cplot
signature(object = "PSTf")
: plot single nodes of a PST, seecplot,PSTf-method
.- generate
signature(object = "PSTf")
: generate artificial sequences, seegenerate,PSTf-method
.- impute
signature(object = "PSTf", data = "stslist")
: impute missing values in sequence data, seeimpute,PSTf,stslist-method
.- logLik
signature(object = "PSTf")
: extract log-likelihood of the VLMC model represented by a PST, seelogLik,PSTf-method
.- nobs
signature(object = "PSTf")
: number of observations (symbols) in the learning sample to which a VLMC model is fitted, seenobs,PSTf-method
.- nodenames
signature(object = "PSTf")
: retrieve the node labels of a PST, see seenodenames,PSTf-method
.- pdist
signature(x = "PSTf", y = "PSTf")
: compute probabilistic divergence between two PSTs, seepdist,PSTf,PSTf-method
.- plot
signature(x = "PSTf", y = "ANY")
: plot a PST, seeplot,PSTf,ANY-method
.- pmine
signature(object = "PSTf", data = "stslist")
: pattern mining, see seepmine,PSTf,stslist-method
.- ppplot
signature(object = "PSTf")
: plotting a branch of a PST, seeppplot,PSTf-method
.- pqplot
signature(object = "PSTf", data = "stslist")
: plot the predicted probability of each state in a sequence, seepqplot,PSTf,stslist-method
.- predict
signature(object = "PSTf")
: predict the likelihood of sequences, seepredict,PSTf-method
.signature(x = "PSTf")
: print a PST, seeprint,PSTf-method
.- prune
signature(object = "PSTf")
: prune a PST, seeprune,PSTf-method
.- query
signature(object = "PSTf")
: retrieve counts or next symbol probability distribution from a node in a Probabilistic Suffix Tree, seequery,PSTf-method
.- subtree
signature(object = "PSTf")
: extract a subtree from a segmented PST, seesubtree,PSTf-method
.- summary
signature(object = "PSTf")
: seesummary,PSTf-method
.- tune
signature(object = "PSTf")
: AIC, AICc and BIC based model selection, seetune,PSTf-method
.
Author(s)
Alexis Gabadinho
See Also
Examples
showClass("PSTf")