/**
* If method parameter n is non-null, then attempt to set distribution parameter <code>N</code> to
* n if n is a nonnegative integer. If method parameter p is non-null, then set distribution
* parameter <code>P</code> to method parameter p.
*
* @param n distribution parameter <code>N</code>, representing the number of categories. Must be
* nonnegative. Can be set multiple times.
* @param p distribution parameter <code>P</code>, representing the column vector of unnormalized
* probabilities.
*/
public void setParams(Number n, MatrixLib p) {
if (n != null) {
if (n.intValue() < 0) {
throw new IllegalArgumentException(
"The number of trials 'n' for a Multinomial Distribution must be nonnegative");
}
this.n = n.intValue();
this.hasN = true;
}
if (p != null) {
if (p.numCols() != 1 || p.numRows() == 0) {
throw new IllegalArgumentException("The vector p passed in is not a column vector");
}
initializeProbabilityVector(p);
this.hasP = true;
}
this.finiteSupport = null;
}
/**
* Precondition: p is a column vector
*
* <p>Sets instance variable p to a normalized array of probabilities Sets pCDF to the CDF of p
*
* @param p
*/
private void initializeProbabilityVector(MatrixLib p) {
double sum = 0.0;
for (int i = 0; i < p.numRows(); i++) {
double ele = p.elementAt(i, 0);
if (ele < 0) {
throw new IllegalArgumentException(
"Probability " + ele + " for element " + i + " is negative.");
}
sum += ele;
}
if (sum < 1e-9) {
throw new IllegalArgumentException("Probabilities sum to approx zero");
}
this.k = p.numRows();
this.p = new double[k];
this.pCDF = new double[k];
this.p[0] = p.elementAt(0, 0) / sum;
this.pCDF[0] = this.p[0];
for (int i = 1; i < p.numRows(); i++) {
this.p[i] = p.elementAt(i, 0) / sum;
this.pCDF[i] = pCDF[i - 1] + this.p[i];
}
}
