Computes the traditional \(\mathcal{L}_2\)-star discrepancy \(\mathcal{D}_2^*(\mathcal{P})\) for a set of \(n\) points \(\mathcal{P}\) [226], [227],. More...
Public Member Functions | |
| double | compute (double[][] points, int n, int s, double[] gamma) |
| Computes the discrepancy of the first n points of points in dimension s with weights gamma. | |
| DiscL2Star (double[][] points, int n, int s) | |
| Constructor with the \(n\) points points[i] in dimension. | |
| DiscL2Star (int n, int s) | |
| Constructor with \(n\) points in dimension \(s\). | |
| DiscL2Star (PointSet set) | |
| Constructor with the point set set. | |
| DiscL2Star () | |
| Empty constructor. | |
| double | compute (double[][] points, int n, int s) |
Computes the traditional \(\mathcal{L}_2\)-star discrepancy ( discstar ) for the first \(n\) points of points, in dimension \(s\). | |
| double | compute (double[] T, int n) |
| Computes the traditional \(\mathcal{L}_2\)-star discrepancy for the set of \(n\) 1-dimensional points. | |
| Public Member Functions inherited from umontreal.ssj.discrepancy.Discrepancy | |
| Discrepancy (double[][] points, int n, int s) | |
| Constructor with the \(n\) points points[i] in \(s\) dimensions. | |
| Discrepancy (double[][] points, int n, int s, double[] gamma) | |
| Constructor with the \(n\) points points[i] in \(s\) dimensions and the \(s\) weight factors gamma[ \(j\)], \(j = 0, 1,
…, (s-1)\). | |
| Discrepancy (int n, int s, double[] gamma) | |
| The number of points is \(n\), the dimension \(s\), and the. | |
| Discrepancy (PointSet set) | |
| Constructor with the point set set. | |
| Discrepancy () | |
| Empty constructor. | |
| double | compute () |
| Computes the discrepancy of all the points in maximal dimension (dimension of the points). | |
| double | compute (int s) |
| Computes the discrepancy of all the points in dimension \(s\). | |
| double | compute (double[][] points) |
| Computes the discrepancy of all the points of points in maximum dimension. | |
| double | compute (double[] T) |
| Computes the discrepancy of all the points of T in 1 dimension. | |
| double | compute (double[] T, int n, double gamma) |
| Computes the discrepancy of the first n points of T in 1 dimension with weight gamma. | |
| double | compute (PointSet set, double[] gamma) |
| Computes the discrepancy of all the points in set in the same dimension as the point set and with weights gamma. | |
| double | compute (PointSet set) |
| Computes the discrepancy of all the points in set in the same dimension as the point set. | |
| int | getNumPoints () |
| Returns the number of points \(n\). | |
| int | getDimension () |
| Returns the dimension of the points \(s\). | |
| void | setPoints (double[][] points, int n, int s) |
| Sets the points to points and the dimension to \(s\). | |
| void | setPoints (double[][] points) |
| Sets the points to points. | |
| void | setGamma (double[] gam, int s) |
| Sets the weight factors to gam for each dimension up to \(s\). | |
| double[] | getGamma () |
| Returns the weight factors gamma for each dimension up to \(s\). | |
| String | toString () |
| Returns the parameters of this class. | |
| String | formatPoints () |
| Returns all the points of this class. | |
| String | getName () |
| Returns the name of the Discrepancy. | |
Additional Inherited Members | |
| Static Public Member Functions inherited from umontreal.ssj.discrepancy.Discrepancy | |
| static double[][] | toArray (PointSet set) |
| Returns all the \(n\) points ( \(s\)-dimensional) of. | |
| static DoubleArrayList | sort (double[] T, int n) |
| Sorts the first \(n\) points of \(T\). | |
Detailed Description
Computes the traditional \(\mathcal{L}_2\)-star discrepancy \(\mathcal{D}_2^*(\mathcal{P})\) for a set of \(n\) points \(\mathcal{P}\) [226], [227],.
[80] . This discrepancy is also known as the Cramér-von Mises goodness-of-fit statistic. Let \(t = [t_1, t_2, …, t_s]\) be the coordinates of a point in \([0, 1]^s\) and define the volume of the parallelepiped anchored at the origin as Vol \(([0,t)) = t_1 t_2 ... t_s\). Let the function \(R_n(t, P)\) be defined as
\[ R_n(t, P) = \frac{1}{n} \sum_{j=1}^n I_{[0, t)^s}(z_j) - \mbox{Vol}([0,t)), \]
where \(I_{[0, t)^s}\) is the indicator function of \([0, t)^s\). \(R_n\) can be described as the difference between the number of points in \([0, t)^s\) and the volume of that subregion. The \(\mathcal{L}_2\)-star discrepancy is defined as \(\mathcal{L}_2\) norm of \(R_n(t, P)\), that is the (REF_discrepancy_DiscL2Star_eq_discstar0)
\[ \mathcal{D}_2^*(\mathcal{P}) = \left(\int_{[0, 1]^s} d^st\; R_n^2(t, P)\right)^{1/2} \tag{discstar0} \]
It can be calculated explicitly to give the
\[ [\mathcal{D}_2^*(\mathcal{P})]^2 = \left(\frac{1}{3}\right)^s - \frac{2}{n} \sum_{i=1}^n \prod_{k=1}^s \left(\frac{1 - z_{ik}^2}{2}\right) + \frac{1}{n^2} \sum_{i=1}^n\sum_{j=1}^n \prod_{k=1}^s \left[1 - \max(z_{ik}, z_{jk})\right], \tag{discstar} \]
where \(n\) is the number of points of \(\mathcal{P}\), \(s\) is the dimension, and \(z_{ik}\) is the \(k\)-th coordinate of point \(i\).
In one dimension, formula (discstar ) is equivalent to the
\[ [\mathcal{D}_2^*(\mathcal{P})]^2 = \frac{1}{12n^2} + \frac{1}{n} \sum_{i=1}^n \left(z_{(i)} - \frac{i - 1/2}{n}\right)^2, \tag{cramermises} \]
where \(n\) is the number of points of \(\mathcal{P}\), and the \(z_{(i)}\) are the points of \(\mathcal{P}\) sorted in increasing order. This formula is faster to compute than the general formula (discstar ).
Definition at line 75 of file DiscL2Star.java.
Constructor & Destructor Documentation
◆ DiscL2Star() [1/4]
| umontreal.ssj.discrepancy.DiscL2Star.DiscL2Star | ( | double | points[][], |
| int | n, | ||
| int | s ) |
Constructor with the \(n\) points points[i] in dimension.
\(s\). points[i][j] is the \(j\)-th coordinate of point \(i\). Both \(i\) and \(j\) start at 0.
Definition at line 87 of file DiscL2Star.java.
◆ DiscL2Star() [2/4]
| umontreal.ssj.discrepancy.DiscL2Star.DiscL2Star | ( | int | n, |
| int | s ) |
Constructor with \(n\) points in dimension \(s\).
The \(n\) points will be chosen later.
Definition at line 95 of file DiscL2Star.java.
◆ DiscL2Star() [3/4]
| umontreal.ssj.discrepancy.DiscL2Star.DiscL2Star | ( | PointSet | set | ) |
Constructor with the point set set.
All the points are copied in an internal array.
Definition at line 103 of file DiscL2Star.java.
◆ DiscL2Star() [4/4]
| umontreal.ssj.discrepancy.DiscL2Star.DiscL2Star | ( | ) |
Empty constructor.
One must set the points and the dimension before calling any method.
Definition at line 111 of file DiscL2Star.java.
Member Function Documentation
◆ compute() [1/3]
| double umontreal.ssj.discrepancy.DiscL2Star.compute | ( | double[] | T, |
| int | n ) |
Computes the traditional \(\mathcal{L}_2\)-star discrepancy for the set of \(n\) 1-dimensional points.
\(T\), using formula ( cramermises ) above. The points of \(T\) must be sorted before calling this method.
Reimplemented from umontreal.ssj.discrepancy.Discrepancy.
Definition at line 165 of file DiscL2Star.java.
◆ compute() [2/3]
| double umontreal.ssj.discrepancy.DiscL2Star.compute | ( | double | points[][], |
| int | n, | ||
| int | s ) |
Computes the traditional \(\mathcal{L}_2\)-star discrepancy ( discstar ) for the first \(n\) points of points, in dimension \(s\).
Reimplemented from umontreal.ssj.discrepancy.Discrepancy.
Definition at line 120 of file DiscL2Star.java.
◆ compute() [3/3]
| double umontreal.ssj.discrepancy.DiscL2Star.compute | ( | double | points[][], |
| int | n, | ||
| int | s, | ||
| double[] | gamma ) |
Computes the discrepancy of the first n points of points in dimension s with weights gamma.
Reimplemented from umontreal.ssj.discrepancy.Discrepancy.
Definition at line 77 of file DiscL2Star.java.
The documentation for this class was generated from the following file:
- src/main/java/umontreal/ssj/discrepancy/DiscL2Star.java
