/**
* Constructs the MetropolisHastingsSimulation object.
*
* @param pModel Pointer to the Model.
* @param pData Pointer to the Data.
*/
MetropolisHastingsSimulation::MetropolisHastingsSimulation(Model* pModel,
Data* pData) :
Simulation(pModel, pData), //
lScores(1, VectorXd(nStatistics())), //
lScoreTargets(VectorXd::Zero(nStatistics())), //
lNeedsDerivative(false), //
lDerivative(1, MatrixXd(nParameters(), nParameters())), //
lMeanScoresMinusTargets(), //
lNRunMH(nPeriods()), //
lResult(&lTheta, &lScoreTargets, 0/*ptr*/, &lScores, 0/*ptr*/,
&lMeanScoresMinusTargets, 0/*ptr*/, 0/*ptr*/, &lDerivative, 0/*ptr*/)
{
// Conditional is not possible with maximum likelihood
// R: sienaModelCreate.r sienaModelCreate() (line ~56)
assert(!pModel->conditional());
// Calculate the number of simulation steps per period.
// R: initializeFran.r initializeFRAN() (line ~504)
const MatrixXd targets = calculateTargetStatistics();
const ArrayXb basicRates = rStatisticEffects().array()
== &Simulation::RATE_EFFECT;
const VectorXd zero = VectorXd::Zero(nStatistics());
for (int m = 0; m < nPeriods(); ++m) {
lNRunMH[m] = N_RUN_MH_MULTIPLICATOR_DEFAULT
* basicRates.select(targets.row(m).transpose(), zero).sum();
if (lNRunMH[m] > 100) {
lNRunMH[m] = round((double) lNRunMH[m] / 100.0) * 100;
}
}
}
/**
* Constructs the StatisticsSimulation object.
*
* @param pModel Pointer to the Model.
* @param pData Pointer to the Data.
* @param nThreads Number of threads used to perform parallel simulations.
*/
StatisticsSimulation::StatisticsSimulation(Model* pModel, Data* pData,
const unsigned int nThreads) :
Simulation(pModel, pData), //
lNThreads(nThreads), //
lEpochSimulations(), //
lSeeds(pData->observationCount() - 1, vector<int>()), //
lTargets(calculateTargetStatistics().colwise().sum()), //
lPeriodWiseTargets(calculateTargetStatistics()), //
lStatistic(), //
lStatisticsData(), //
lStatistics(), //
lScoresData(), //
lScores(), //
lTimesData(), //
lTimes(), //
lMeanStatisticsMinusTargets(nStatistics()), //
lResult(&lTheta, &lTargets, &lPeriodWiseTargets, &lStatistic, &lStatistics,
&lMeanStatisticsMinusTargets, &lSeeds, &lScores, 0/*ptr*/, &lTimes) {
assert(lNThreads > 0);
resizeEpochSimulations(lNThreads);
// Setup the mapped matrices for statistics and time. Statistics is always
// needed.
LOG(Priority::DEBUG, "setup mapped statistics vector");
setupMaps(lStatistics, lStatisticsData, lNThreads, nPeriods(),
nStatistics());
// Conditional is not changed during phases, so no later change required.
if (lpModel->conditional()) {
LOG(Priority::DEBUG, "setup mapped times vector");
setupMaps(lTimes, lTimesData, lNThreads, nPeriods(), 1);
}
// Score might not be needed if they are needsChanged, creates the stores.
int n = lpModel->needScores() ? lNThreads : 0;
setupMaps(lScores, lScoresData, n, nPeriods(), nParameters());
static MeanStatisticsCalculator s;
addResultModificator(&s);
}
