Description Objects from the Class Slots Extends Methods Author(s) References See Also Examples
This class contains data simulated from the RtreemixModel
it
extends together with their sampling and waiting times. It also
includes the sampling mode and the sampling parameter used for the time simulation.
Objects can be created by calls of the form new("RtreemixSim",
Model, SimPatterns, SamplingMode, SamplingParam, WaitingTimes,
SamplingTimes)
.
The RtreemixSim
class specifies patterns (RtreemixData
)
simulated from the parent RtreemixModel
together with their
waiting and sampling times resulting from the waiting time simulation
along the branchings in the parent model.
The Model
is an RtreemixModel
object used in the data
and time simulation process. In other words, this model is used for
simulating patterns with their sampling and waiting times.
The SimPatterns
is an RtreemixData
object that contains
the patterns simulated from the given Model
.
The SamplingMode
is a character
that specifies the
sampling mode ("constant" or "exponential") used in the time simulations.
The SamplingParam
is a numeric
that specifies the
sampling parameter corresponding to the sampling mode given by
SamplingMode
.
The WaitingTimes
is a numeric vector
that specifies the
waiting times for the simulated patterns. Its length equals the number
of patterns in SimPatterns
.
The SamplingTimes
is a numeric vector
that specifies the
sampling times for the simulated patterns. Its length equals the number
of patterns in SimPatterns
.
SimPatterns
:Object of class "RtreemixData"
.
SamplingMode
:Object of class "character"
. It
can have one of the two possible values: "constant" or "exponential".
SamplingParam
:Object of class "numeric"
.
WaitingTimes
:Object of class "numeric"
. The
length of WaitingTimes
must be equal to the number
of patterns in SimPatterns
.
SamplingTimes
:Object of class "numeric"
. The
length of SamplingTimes
must be equal to the number
of patterns in SimPatterns
.
Class "RtreemixModel"
, directly.
Class "RtreemixData"
, by class "RtreemixModel", distance 2.
signature(object = "RtreemixSim")
: A
method for obtaining the sampling mode ("constant" or
"exponential") used for the time simulations.
signature(object = "RtreemixSim")
: A
method for obtaining the sampling parameter corresponding to the
specified SamplingMode
.
signature(object = "RtreemixSim")
: A
method used for obtaining the sampling times of the patterns
in SimPatterns
.
signature(object = "RtreemixSim")
: A
method used for obtaining the patterns simulated from the parent model.
signature(object = "RtreemixSim")
: A
method used for obtaining the waiting times of the patterns
in SimPatterns
.
signature(object = "RtreemixSim")
: A method
for obtaining the mixture model used in the simulations.
signature(object = "RtreemixSim")
: A method
for obtaining the number of simulated patterns, i.e. the size of SimPatterns
.
Jasmina Bogojeska
Learning multiple evolutionary pathways from cross-sectional data, N. Beerenwinkel et al.
RtreemixGPS-class
, RtreemixData-class
,
RtreemixModel-class
,
fit-methods
, sim-methods
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## Generate a random RtreemixModel object with 3 components and 9 genetic events.
rand.mod <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob = c(0.2, 0.8))
show(rand.mod)
## Create an RtreemixSim object by simulating patterns with their sampling and waiting times from a given mixture model.
sim.data <- sim(model = rand.mod, sampling.mode = "exponential", sampling.param = 1, no.sim = 200)
show(sim.data)
## See the slots from the RtreemixSim object.
SimPatterns(sim.data)
SamplingMode(sim.data)
SamplingParam(sim.data)
WaitingTimes(sim.data)
SamplingTimes(sim.data)
## See model.
getModel(sim.data)
## See number of simulated patterns.
noDraws(sim.data)
|
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