@Test public void testMissings() { int n = 120; DataBlock k = new DataBlock(n); k.randomize(0); int m = 0; for (int i = 0; i < n - 5; i += n / 3) { k.set(i, Double.NaN); ++m; } for (int i = n - 5; i < n; ++i) { k.set(i, Double.NaN); ++m; } Matrix J = DifferenceStationaryModelHelper.missings(k); assertTrue(J.getRowsCount() == n - m); }
public static Matrix missings(final IReadDataBlock data) { return missings(data, null); }
DifferenceStationaryModelHelper { public static Matrix missings(final IReadDataBlock data) { return missings(data, null); } }
DifferenceStationaryModelHelper { public static Matrix missings(final IReadDataBlock data) { return missings(data, null); } DifferenceStationaryModelHelper(final DataBlock y, final Matrix X, final Matrix transformation, final BackFilter difference);  DifferenceStationaryModelHelper(final IModelProvider provider); }
DifferenceStationaryModelHelper { public static Matrix missings(final IReadDataBlock data) { return missings(data, null); } DifferenceStationaryModelHelper(final DataBlock y, final Matrix X, final Matrix transformation, final BackFilter difference);  DifferenceStationaryModelHelper(final IModelProvider provider); static Matrix missings(final IReadDataBlock data); static Matrix missings(final IReadDataBlock data, final int[] inits); static Matrix last(final int len, final int step); static Matrix first(final int len, final int step); static Matrix aggregation(final int len, final int nagg); static int[] searchDefaultInitialValues(IReadDataBlock y, int d); Matrix getB(); Matrix getD(); ConcentratedLikelihood compute(Matrix Vw); Matrix computeProjections(Matrix Z, Matrix Vw); }
DifferenceStationaryModelHelper { public static Matrix missings(final IReadDataBlock data) { return missings(data, null); } DifferenceStationaryModelHelper(final DataBlock y, final Matrix X, final Matrix transformation, final BackFilter difference);  DifferenceStationaryModelHelper(final IModelProvider provider); static Matrix missings(final IReadDataBlock data); static Matrix missings(final IReadDataBlock data, final int[] inits); static Matrix last(final int len, final int step); static Matrix first(final int len, final int step); static Matrix aggregation(final int len, final int nagg); static int[] searchDefaultInitialValues(IReadDataBlock y, int d); Matrix getB(); Matrix getD(); ConcentratedLikelihood compute(Matrix Vw); Matrix computeProjections(Matrix Z, Matrix Vw);  }