/**
* Calculates the p-value of null Hypothesis
*
* @param flatDataCollection
* @param median
* @return
* @throws IllegalArgumentException
*/
public static double getPvalue(FlatDataCollection flatDataCollection, double median)
throws IllegalArgumentException {
int n = 0;
AssociativeArray Di = new AssociativeArray();
Iterator<Double> it = flatDataCollection.iteratorDouble();
while (it.hasNext()) {
double delta = it.next() - median;
if (delta == 0.0) {
continue; // don't count it at all
}
String key = "+";
if (delta < 0) {
key = "-";
}
Di.put(key + String.valueOf(n), Math.abs(delta));
++n;
}
if (n <= 0) {
throw new IllegalArgumentException();
}
// converts the values of the table with its Ranks
Di.toFlatDataList();
Ranks.getRanksFromValues(Di);
double W = 0.0;
for (Map.Entry<Object, Object> entry : Di.entrySet()) {
String key = entry.getKey().toString();
Double rank = TypeInference.toDouble(entry.getValue());
if (key.charAt(0) == '+') {
W += rank;
}
}
double pvalue = scoreToPvalue(W, n);
return pvalue;
}
/**
* Calculates the score of Chisquare test.
*
* @param dataTable
* @return
* @throws IllegalArgumentException
*/
public static AssociativeArray getScore(DataTable2D dataTable) throws IllegalArgumentException {
if (dataTable.isValid() == false) {
throw new IllegalArgumentException();
}
// Estimate marginal scores and sum
Map<Object, Double> XdotJ = new HashMap<>();
Map<Object, Double> XIdot = new HashMap<>();
double Xdotdot = 0.0;
for (Map.Entry<Object, AssociativeArray> entry1 : dataTable.entrySet()) {
Object i = entry1.getKey();
AssociativeArray row = entry1.getValue();
for (Map.Entry<Object, Object> entry2 : row.entrySet()) {
Object j = entry2.getKey();
Object value = entry2.getValue();
double v = Dataset.toDouble(value);
// Summing the columns
if (XdotJ.containsKey(j) == false) {
XdotJ.put(j, v);
} else {
XdotJ.put(j, XdotJ.get(j) + v);
}
// Summing the rows
if (XIdot.containsKey(i) == false) {
XIdot.put(i, v);
} else {
XIdot.put(i, XIdot.get(i) + v);
}
Xdotdot += v;
}
}
int k = XdotJ.size();
int n = XIdot.size();
// Calculating Chisquare score
double ChisquareScore = 0.0;
if (k == 2
&& n
== 2) { // if 2x2 then perform the Yates correction. Make this check outside the loops
// to make it faster
for (Map.Entry<Object, AssociativeArray> entry1 : dataTable.entrySet()) {
Object i = entry1.getKey();
AssociativeArray row = entry1.getValue();
for (Map.Entry<Object, Object> entry2 : row.entrySet()) {
Object j = entry2.getKey();
Object value = entry2.getValue();
double v = Dataset.toDouble(value);
// expected value under null hypothesis
double eij = XIdot.get(i) * XdotJ.get(j) / Xdotdot;
if (eij == 0) {
continue;
}
ChisquareScore += Math.pow((Math.abs(v - eij) - 0.5), 2) / eij;
}
}
} else {
for (Map.Entry<Object, AssociativeArray> entry1 : dataTable.entrySet()) {
Object i = entry1.getKey();
AssociativeArray row = entry1.getValue();
for (Map.Entry<Object, Object> entry2 : row.entrySet()) {
Object j = entry2.getKey();
Object value = entry2.getValue();
double v = Dataset.toDouble(value);
// expected value under null hypothesis
double eij = XIdot.get(i) * XdotJ.get(j) / Xdotdot;
ChisquareScore += Math.pow((v - eij), 2) / eij;
}
}
}
XdotJ = null;
XIdot = null;
AssociativeArray result = new AssociativeArray();
result.put("k", k);
result.put("n", n);
result.put("score", ChisquareScore);
return result;
}
