march.mtd.construct {march}

Construct a Mixture Transition Distribution (MTD) model.

Description

A Mixture Transition Distribution model (march.Mtd-class) object of order order is constructed according to a given march.Dataset-class y. The first maxOrder-order elements of each sequence are truncated in order to return a model which can be compared with other Markovian models of visible order maxOrder.

Usage

march.mtd.construct(
  y,
  order,
  maxOrder = order,
  mtdg = FALSE,
  MCovar = 0,
  init = "best",
  deltaStop = 1e-04,
  llStop = 0.01,
  maxIter = 0,
  seedModel = NULL
)

Arguments

y

the dataset (march.Dataset-class) from which to construct the model.

order

the order of the constructed model.

maxOrder

the maximum visible order among the set of Markovian models to compare.

mtdg

flag indicating whether the constructed model should be a MTDg using a different transition matrix for each lag (value: TRUE or FALSE).

MCovar

vector of the size Ncov indicating which covariables are used (0: no, 1:yes)

init

the init method, to choose among best, random and weighted.

deltaStop

the delta below which the optimization phases of phi and Q stop.

llStop

the ll increase below which the EM algorithm stop.

maxIter

the maximal number of iterations of the optimisation algorithm (zero for no maximal number).

seedModel

an object containing a MTD or a DCMM model used to initialize the parameters of the MTD model.

Author(s)

Ogier Maitre, Kevin Emery, Andre Berchtold

See Also

march.Mtd-class, march.Model-class, march.Dataset-class.

Examples

# Build a 4th order MTD model from the pewee data set.
model <- march.mtd.construct(pewee,4)
print(model)

# Build a 3th order MTDg model from the pewee data set.
model <- march.mtd.construct(pewee,3,mtdg=TRUE)
print(model)