/**
* Constructs a new Fisher Z independence test with the listed arguments.
*
* @param data A 2D continuous data set with no missing values.
* @param variables A list of variables, a subset of the variables of <code>data</code>.
* @param alpha The significance cutoff level. p values less than alpha will be reported as
* dependent.
*/
public IndTestFisherZShortTriangular(TetradMatrix data, List<Node> variables, double alpha) {
DataSet dataSet = ColtDataSet.makeContinuousData(variables, data);
this.covMatrix = new ShortTriangularMatrix(dataSet.getNumColumns());
this.covMatrix.becomeCorrelationMatrix(dataSet);
this.variables = dataSet.getVariables();
setAlpha(alpha);
this.deterministicTest = new IndTestFisherZGeneralizedInverse(dataSet, alpha);
}
/**
* @param sampleSize The sample size of the desired data set.
* @param latentDataSaved True if latent variables should be included in the data set.
* @return This returns a standardized data set simulated from the model, using the reduced form
* method.
*/
public DataSet simulateDataReducedForm(int sampleSize, boolean latentDataSaved) {
int numVars = getVariableNodes().size();
// Calculate inv(I - edgeCoef)
TetradMatrix edgeCoef = edgeCoef().copy().transpose();
// TetradMatrix iMinusB = TetradAlgebra.identity(edgeCoef.rows());
// iMinusB.assign(edgeCoef, Functions.minus);
TetradMatrix iMinusB = TetradAlgebra.identity(edgeCoef.rows()).minus(edgeCoef);
TetradMatrix inv = iMinusB.inverse();
// Pick error values e, for each calculate inv * e.
TetradMatrix sim = new TetradMatrix(sampleSize, numVars);
// Generate error data with the right variances and covariances, then override this
// with error data for varaibles that have special distributions defined. Not ideal,
// but not sure what else to do at the moment. It's better than not taking covariances
// into account!
TetradMatrix cholesky = MatrixUtils.choleskyC(errCovar(errorVariances()));
for (int i = 0; i < sampleSize; i++) {
TetradVector e = new TetradVector(exogenousData(cholesky, RandomUtil.getInstance()));
TetradVector ePrime = inv.times(e);
sim.assignRow(i, ePrime); // sim.viewRow(i).assign(ePrime);
}
DataSet fullDataSet = ColtDataSet.makeContinuousData(getVariableNodes(), sim);
if (latentDataSaved) {
return fullDataSet;
} else {
return DataUtils.restrictToMeasured(fullDataSet);
}
}