RSiena (version 1.1-212)

sienaModelCreate: Function to create an object containing the algorithm specifications for parameter estimation in RSiena

Description

Creates an object with specifications for the algorithm for parameter estimation in RSiena.

Usage

sienaModelCreate(fn, projname = "Siena", MaxDegree = 0,
     useStdInits = FALSE, n3 = 1000, nsub = 4, maxlike = FALSE,
     diag = !maxlike, condvarno = 0, condname = "", firstg = 0.2,
     cond = NA, findiff = FALSE, seed = NULL, pridg=0.05,
     prcdg=0.05, prper=0.2, pripr=0.3, prdpr=0.3, prirms=0.05,
     prdrms=0.05, maximumPermutationLength=40,
     minimumPermutationLength=2, initialPermutationLength=20,
     modelType=1, mult=5)

Value

Returns a model object of class "sienaModel" containing:projnameString value of name of project.useStdInitsBoolean, see above.checktimeBoolean, set to TRUE: report time in the phases or not.n3number of iterations in Phase 3firstgInitial value of the scaling ('gain') parameter in the Robbins-Monro algorithm.maxratValue used to control the maximum size of the jumps.maxmaxratValue used to control the maximum size of the jumps.maxlikeBoolean: is FRAN using maximum likelihood?FRANnameName of simulation function FRAN. Is derived by sienaModelCreate from fn and maxlike.cconditionalBoolean: is FRAN using conditional estimation?condvarnoNumber of dependent variable on which to condition.condnameName of dependent variable on which to condition.FinDiff.methodBoolean: are derivatives calculated using finite differences?nsubNumber of subphases in phase 2.diagBoolean: use only the diagonal of the derivative matrix?modelTypeType of model to be fitted: 1=directed, 2:6 for symmetric networks: 2=forcing, 3=Initiative model, 4=Pairwise forcing model, 5=Pairwise mutual model, 6=Pairwise joint modelMaxDegreeNamed vector of maximum degree values, or NULL.randomSeedInteger. Starting value of random seed. Not present unless given in call.pridgReal number. Probability used in Metropolis-Hastings routine in ML estimation.prcdgReal number. Probability used in Metropolis-Hastings routine in ML estimation.prperReal number. Probability used in Metropolis-Hastings routine in ML estimation.priprReal number. Probability used in Metropolis-Hastings routine in ML estimation.prdprReal number. Probability used in Metropolis-Hastings routine in ML estimation.prirmsReal number. Probability used in Metropolis-Hastings routine in ML estimation.prdrmsReal number. Probability used in Metropolis-Hastings routine in ML estimation.maximumPermutationLengthMaximum length of permutation in steps in ML estimationminimumPermutationLengthMinimum length of permutation in steps in ML estimationinitialPermutationLengthInitial length of permutation in steps in ML estimationmultMultiplication factor for maximum likelihood. Number of steps per iteration is set to this multiple of the total distance between the observations at start and finish of the wave.

Details

Model specification is done via this object for siena07. This function creates an object with the elements required to control the Robbins-Monro algorithm. Those not available as arguments can be changed manually where desired.

References

See http://www.stats.ox.ac.uk/~snijders/siena/

See Also

This is for use in siena07.

Examples

mymodel <- sienaModelCreate(projname="NetworkDyn")
StdModel <- sienaModelCreate(projname="NetworkDyn",useStdInits=TRUE)
CondModel <- sienaModelCreate(projname="NetworkDyn",condvarno=1,cond=TRUE)
Max10Model <- sienaModelCreate(projname="NetworkDyn",MaxDegree=c(mynet=10))
# where mynet is the name of the network object created by sienaNet().