A strategy is a way to find a good estimate of the parameters of a mixture model when using an EM algorithm or its variants. A ``try'' is composed of three stages
nbShortRun short iterations of the initialization step and
of the EM, CEM, SEM or SemiSEM algorithm.
nbInit initializations using the [clusterInit] method.
A long run of the EM, CEM, SEM or SemiSEM algorithm.
For example if nbInit is 5 and nbShortRun is also 5, there will
be 5 packets of 5 models initialized. In each packet, the best model will be
ameliorated using a short run. Among the 5 models ameliorated the best one will be
estimated until convergence using a long run. In total there will be 25 initializations,
5 short runs and one long-run.
clusterSemiSEMStrategy() create an instance of [ClusterStrategy]
for users with many missing values uning a semiSem algorithm.
clusterSEMStrategy() create an instance of [ClusterStrategy]
for users with many missing values using a SEM algorithm.
clusterFastStrategy() create an instance of [ClusterStrategy] for impatient user.
clusterStrategy(
nbTry = 1,
nbInit = 5,
initMethod = "class",
initAlgo = "EM",
nbInitIteration = 20,
initEpsilon = 0.01,
nbShortRun = 5,
shortRunAlgo = "EM",
nbShortIteration = 100,
shortEpsilon = 1e-04,
longRunAlgo = "EM",
nbLongIteration = 1000,
longEpsilon = 1e-07
)clusterSemiSEMStrategy()
clusterSEMStrategy()
clusterFastStrategy()
a [ClusterStrategy] object
number of estimation to attempt.
Integer defining the number of initialization to try. Default value: 5.
Character string with the initialization method, see [clusterInit]$
for possible values. Default value: "class".
Character string with the algorithm to use in the initialization stage,
[clusterAlgo] for possible values. Default value: "EM".
Integer defining the maximal number of iterations in
initialization algorithm. If initAlgo = "EM", "CEM" or "SemiSEM", this
is the number of iterations if initAlgo = "SEM". Default value: 20.
Real defining the epsilon value for the algorithm.
initEpsilon is not used by the SEM algorithm. Default value: 0.01.
Integer defining the number of short run to try (the strategy launch an initialization before each short run). Default value: 5.
A character string with the algorithm to use in the short run stage. Default value: "EM".
Integer defining the maximal number of iterations in
a short run if shortRunAlgo = "EM", "CEM" or "semiSEM", or the number
of iterations if shortRunAlgo = "SEM". Default value: 100.
Real defining the epsilon value for the algorithm.
shortEpsilon is not used by the SEM algorithm. Default value: 1e-04.
A character string with the algorithm to use in the long run stage Default value: "EM".
Integer defining the maximal number of iterations in the short runs
if shortRunAlgo = "EM", "CEM" or "SemiSEM", or the number of iterations
if shortRunAlgo = "SEM". Default value: 1000.
Real defining the epsilon value for the algorithm.
longEpsilon is not used by the SEM algorithm. Default value: 1e-07.
Serge Iovleff
The whole process can be repeated at least nbTry times. If a try
success, the estimated model is returned, otherwise an empty model is returned
(with an error message).
clusterStrategy()
clusterStrategy(longRunAlgo= "CEM", nbLongIteration=100)
clusterStrategy(nbTry = 1, nbInit= 1, shortRunAlgo= "SEM", nbShortIteration=100)
clusterSemiSEMStrategy()
clusterSEMStrategy()
clusterFastStrategy()
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