simstats0c: Versions of FRAN
In RSiena: Siena - Simulation Investigation for Empirical Network Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

The functions to be called as "FRAN" by siena07. They call compiled C++.

simstats0c(z, x, data=NULL, effects=NULL, fromFiniteDiff=FALSE,
           returnDeps=FALSE, returnChains=FALSE, byWave=FALSE,
           returnDataFrame=FALSE, returnLoglik=FALSE)
maxlikec(z, x, data=NULL, effects=NULL,
           returnChains=FALSE, byGroup = FALSE, byWave=FALSE,
           returnDataFrame=FALSE, returnLoglik=FALSE,
           onlyLoglik=FALSE)
initializeFRAN(z, x, data, effects, prevAns = NULL, initC,
           profileData = FALSE, returnDeps = FALSE, returnChains =
           FALSE, byGroup = FALSE, returnDataFrame = FALSE,
           byWave = FALSE, returnLoglik = FALSE,  onlyLoglik = FALSE)
terminateFRAN(z, x)

`z`	Control object, passed in automatically in `siena07`.
`x`	A sienaAlgorithm object, passed in automatically in `siena07`.
`data`	A sienaData object as returned by `sienaDataCreate`.
`effects`	A sienaEffects object as returned by `getEffects`.
`fromFiniteDiff`	Boolean used during calculation of derivatives by finite differences. Not for user use.
`returnDeps`	Boolean. Whether to return the simulated networks in Phase 3.
`returnChains`	Boolean. Whether to return the chains.
`byWave`	Boolean. Whether to return the finite difference or maximum likelihood derivatives by wave (uses a great deal of memory). Only necessary for `sienaTimeTest`
`byGroup`	Boolean. For internal use: allows different thetas for each group to be used in sienaBayes.
`returnDataFrame`	Boolean. Whether to return the chains as lists or data frames.
`returnLoglik`	Boolean. Whether to return the log likelihood of the simulated chain.
`onlyLoglik`	Boolean: whether to return just the likelihood for the simulated chain, plus details of steps accepted and rejected.
`prevAns`	An object of class "sienaFit" as returned by `siena07`, from which scaling information (derivative matrix and standard deviation of the deviations) will be extracted along with the latest version of the parameters which will be used as the initial values, unless the model requests the use of standard initial values. If the previous model is exactly the same as the current one, Phase 1 will be omitted. If not, any parameter estimates for effects which are included in the new model will be used as initial values, but phase 1 will still be carried out. If the results used as `prevAns` are a reasonable starting point, this will increase the efficiency of the algorithm.
`initC`	If TRUE, call is to setup the data and model in C++. For use with multiple processes only.
`profileData`	Boolean to force dumping of the data for profiling with `sienaProfile.exe`.

Not for general users' use.
The name of simstats0c or maxlikec should be used for the element FRAN of the model object, the former when using estimation by forward simulation, the latter for maximum likelihood estimation. The arguments with no defaults must be passed in on the call to siena07. initializeFRAN and terminateFRAN are called in both cases.

simstats0c returns a list containing:

`fra`	Simulated statistics.
`sc`	Scores with which to calculate the derivative (not phase 2 or if using finite differences or maximum likelihood).
`dff`	Contributions to the derivative if finite differences
`ntim`	For conditional processing, time taken.
`feasible`	Currently set to TRUE.
`OK`	Could be set to FALSE if serious error has occurred.
`sims`	A list of simulation results, one for each period. Each list consists of a list for each data object, each of which consists of a list for each network, each of which consists of a list for each period, each component of which is an edgelist in matrix form (the columns are from, to, value) (or vector for behavior variables). Only if `returnDeps` is TRUE.

maxlikec returns a list containing:

`fra`	Simulated scores.
`dff`	Simulated Hessians: stored as lower triangular matrices
`ntim`	NULL, compatibility only
`feasible`	Currently set to TRUE.
`OK`	Could be set to FALSE if serious error has occurred.
`dff`	Simulated Hessian
`sims`	NULL, for compatibility only
`chain`	A list of sampled chains, one for each period. Each list consists of a list for each data object, each of which consists of a list for each network, each of which consists of a list for each period, each component of which is a list or a data frame depending on the value of `returnDataFrame`. Only if `returnChainss` is TRUE.
`accepts`	Number of accepted MH steps by dependent variable (permute steps are counted under first dependent variable)
`rejects`	Number of rejected MH steps by dependent variable (permute steps are counted under first dependent variable)
`aborts`	Number of aborted MH steps counted under first dependent variable.
`loglik`	Loglikelihood of the simulations. Only if `returnLoglik` is TRUE. If `onlyLoglik` is TRUE, only `loglik`, `accepts`,`rejects` and `aborts` are returned.

initializeFRAN and terminateFRAN return the control object z.

Ruth Ripley

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

siena07

mynet1 <- sienaNet(array(c(tmp3, tmp4), dim=c(32, 32, 2)))
mydata <- sienaDataCreate(mynet1)
myeff <- getEffects(mydata)
myeff <- includeEffects(myeff, transTrip)
myalgorithm <- sienaAlgorithmCreate(fn=simstats0c, nsub=2, n3=100, projname=NULL)
ans <- siena07(myalgorithm, data=mydata, effects=myeff,  batch=TRUE)