public void TauB_SameOrder()
{
var kendall = new KendallTauCorrelation <int, int>(
(int value) => value,
(int value) => value * 10
);
Assert.AreEqual(
1.0,
kendall.TauB(OneToTen),
"Numbers that sort in the same order should be perfectly correlated."
);
}
public void TauB_ReverseOrder()
{
var kendall = new KendallTauCorrelation <int, int>(
(int value) => value,
(int value) => value * -10
);
Assert.AreEqual(
-1.0,
kendall.TauB(OneToTen),
"Numbers that sort in reverse order should be perfectly anti-correlated."
);
}
public void TauB_OneSwap_NoTies()
{
var reordered = new[] { 1, 2, 3, 5, 4, 6, 7, 8, 9, 10 };
var kendall = new KendallTauCorrelation <int, int>(
(int value) => value,
(int value) => reordered[value - 1]
);
Assert.AreEqual(
43.0 / 45.0,
kendall.TauB(OneToTen),
0.00001,
"If a single number is out of place the sequences should be almost perfectly correlated."
);
}
public void TauB_Ties()
{
var reordered = new[] { 1, 1, 1, 4, 5, 6, 7, 8, 9, 10 };
var kendall = new KendallTauCorrelation <int, int>(
(int value) => value,
(int value) => reordered[value - 1]
);
Assert.AreEqual(
42.0 / Sqrt(42.0 * 45.0),
kendall.TauB(OneToTen),
0.00001,
"Adding a few ties should be almost perfectly correlated."
);
}
