SSJ
3.3.1
Stochastic Simulation in Java
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This class computes the discrepancy for randomly shifted, then baker folded points of a set \(\mathcal{P}\). More...
Public Member Functions | |
DiscShiftBaker1 (double[][] points, int n, int s) | |
Constructor with the \(n\) points points[i] in \(s\) dimensions, with all the weights \(\gamma_r = 1\). More... | |
DiscShiftBaker1 (double[][] points, int n, int s, double[] gamma) | |
Constructor with the \(n\) points points[i] in \(s\) dimensions, with weights \(\gamma_r = \) gamma[r-1] . More... | |
DiscShiftBaker1 (int n, int s, double[] gamma) | |
The number of points is \(n\), the dimension \(s\), and the \(s\) weight factors are gamma[ \(r\)] , \(r = 0, 1, …, (s-1)\). More... | |
DiscShiftBaker1 (PointSet set) | |
Constructor with the point set set . More... | |
DiscShiftBaker1 () | |
Empty constructor. More... | |
double | compute (double[][] points, int n, int s) |
Computes the discrepancy ( baker1 ) for the \(s\)-dimensional points of set points , containing \(n\) points. More... | |
double | compute (double[][] points, int n, int s, double[] gamma) |
Computes the discrepancy ( baker1 ) for the first \(n\) points of points in dimension \(s\) and with weight \(\gamma_r = \) gamma[r-1] . | |
double | compute (double[] T, int n) |
Computes the discrepancy ( baker1dim1 ) for the first \(n\) points of \(T\) in 1 dimension, with weight \(\gamma= 1\). | |
double | compute (double[] T, int n, double gamma) |
Computes the discrepancy ( baker1dim1 ) for the first \(n\) points of \(T\) in 1 dimension, with weight \(\gamma=\) gamma . | |
Public Member Functions inherited from Discrepancy | |
Discrepancy (double[][] points, int n, int s) | |
Constructor with the \(n\) points points[i] in \(s\) dimensions. More... | |
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[ \(j\)] , \(j = 0, 1, …, (s-1)\). More... | |
Discrepancy (int n, int s, double[] gamma) | |
The number of points is \(n\), the dimension \(s\), and the \(s\) weight factors are gamma[ \(j\)] , \(j = 0, 1, …, (s-1)\). More... | |
Discrepancy (PointSet set) | |
Constructor with the point set set . More... | |
Discrepancy () | |
Empty constructor. More... | |
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, int n, int s, double[] gamma) |
Computes the discrepancy of the first n points of points in dimension s with weights gamma . | |
abstract double | compute (double[][] points, int n, int s) |
Computes the discrepancy of the first n points of points in dimension s with weights \(=1\). | |
double | compute (double[][] points) |
Computes the discrepancy of all the points of points in maximum dimension. More... | |
double | compute (double[] T, int n) |
Computes the discrepancy of the first n points of T in 1 dimension. More... | |
double | compute (double[] T) |
Computes the discrepancy of all the points of T in 1 dimension. More... | |
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. More... | |
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 \(s\). More... | |
void | setPoints (double[][] points) |
Sets the points to points . More... | |
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. | |
Static Protected Member Functions | |
static double [] | setC (double gam) |
static void | setC (double[] C1, double[] C2, double[] C3, double[] gam, int s) |
Static Protected Member Functions inherited from Discrepancy | |
static void | setONES (int s) |
Additional Inherited Members | |
Static Public Member Functions inherited from Discrepancy | |
static double [][] | toArray (PointSet set) |
Returns all the \(n\) points ( \(s\)-dimensional) of umontreal.ssj.hups.PointSet set as an array points[ \(n\)][ \(s\)] . | |
static DoubleArrayList | sort (double[] T, int n) |
Sorts the first \(n\) points of \(T\). More... | |
Protected Member Functions inherited from Discrepancy | |
void | appendGamma (StringBuffer sb, double[] gamma, int s) |
Protected Attributes inherited from Discrepancy | |
double [] | gamma |
double [][] | Points |
int | dim |
int | numPoints |
Static Protected Attributes inherited from Discrepancy | |
static double [] | ONES = { 1 } |
Static Package Attributes inherited from Discrepancy | |
static final double | UNSIX = 1.0/6.0 |
static final double | QUARAN = 1.0/42.0 |
static final double | UNTRENTE = 1.0 / 30.0 |
static final double | DTIERS = 2.0 / 3.0 |
static final double | STIERS = 7.0 / 3.0 |
static final double | QTIERS = 14.0 / 3.0 |
This class computes the discrepancy for randomly shifted, then baker folded points of a set \(\mathcal{P}\).
It is given by [84] (eq. 15)
\begin{align} [\mathcal{D}(\mathcal{P})]^2 & = -1 + \frac{1}{n^2} \sum_{i=1}^n \sum_{j=1}^n \prod_{r=1}^s \left(1 - \frac{4\gamma_r^2}{3} \left[B_4(\{x_{ir} - x_{jr}\}) - B_4(\{\{x_{ir} - x_{jr}\}-1/2\})\right]\right. \nonumber \\ & \qquad\qquad{} - \frac{\gamma_r^4}{9} \left[7B_4(\{x_{ir} - x_{jr}\}) - 2B_4(\{\{x_{ir} - x_{jr}\}-1/2\})\right] \tag{baker1} \\ & \qquad\qquad{} \left. {} - \frac{16\gamma_r^4}{45} \left[B_6(\{x_{ir} - x_{jr}\}) -B_6(\{\{x_{ir} - x_{jr}\}-1/2\})\right] \right)\nonumber, \end{align}
where \(n\) is the number of points of \(\mathcal{P}\), \(s\) is the dimension of the points, \(x_{ir}\) is the \(r\)-th coordinate of point \(i\), and the \(\gamma_r\) are arbitrary positive weights. The \(B_{\alpha}(x)\) are the Bernoulli polynomials [1] (chap. 23) of degree \(\alpha\) (see umontreal.ssj.util.Num.bernoulliPoly in class util/Num
), and the notation \(\{x\}\) means the fractional part of \(x\), defined here as \(\{x\} = x \bmod1\). In one dimension, the formula simplifies to
\begin{align} [\mathcal{D}(\mathcal{P})]^2 & = \frac{1}{n^2} \sum_{i=1}^n \sum_{j=1}^n \left[ - \frac{4\gamma^2}{3} \left[B_4(\{x_i - x_j\}) - B_4(\{\{x_i - x_j\}-1/2\})\right]\right. \nonumber \\ & \qquad\qquad{} - \frac{\gamma^4}{9} \left[7B_4(\{x_i - x_j\}) - 2B_4(\{\{x_i - x_j\}-1/2\})\right] \tag{baker1dim1} \\ & \qquad\qquad{} \left. {} - \frac{16\gamma^4}{45} \left[B_6(\{x_i - x_j\}) -B_6(\{\{x_i - x_j\}-1/2\})\right] \right]\nonumber. \end{align}
The discrepancy represents a worst-case error criterion for the approximation of integrals, when the integrands have a certain degree of smoothness and lie in a Hilbert space \(\mathcal{H}\) with a reproducing kernel \(K\) given by
\[ K(\mathbf{x},\mathbf{y}) = \prod_{r=1}^s \left[ - \frac{\gamma_r^4}{4!} B_4(\{x_r-y_r\}) + \sum_{\alpha=0}^2 \frac{\gamma_r^{2\alpha}}{(\alpha!)^2} B_{\alpha}(x_r)B_{\alpha}(y_r) \right], \]
The norm of the vectors in \(\mathcal{H}\) is defined by
\[ \| f\|^2 = \sum_{u \subseteq S}\sum_{v \subseteq u}\gamma_u^{-2}\gamma_v^{-2} \int_{[0,1]^v}d\mathbf{x}_v\left[\int_{[0,1]^{S-v}} \frac{\partial^{|u| + |v|}f}{\partial\mathbf{x}_u\partial\mathbf{x}_v} d\mathbf{x}_{S-v} \right]^2, \]
where \(S= \{1, …, s\}\) is a set of coordinate indices, \(u \subseteq S\), and \(\gamma_u = \prod_{r\in u} \gamma_r\).
DiscShiftBaker1 | ( | double | points[][], |
int | n, | ||
int | s | ||
) |
Constructor with the \(n\) points points[i]
in \(s\) dimensions, with all the weights \(\gamma_r = 1\).
points[i][r]
is the r
-th coordinate of point i
. Indices i
and r
start at 0.
DiscShiftBaker1 | ( | double | points[][], |
int | n, | ||
int | s, | ||
double [] | gamma | ||
) |
Constructor with the \(n\) points points[i]
in \(s\) dimensions, with weights \(\gamma_r = \) gamma[r-1]
.
points[i][r]
is the r
-th coordinate of point i
. Indices i
and r
start at 0.
DiscShiftBaker1 | ( | int | n, |
int | s, | ||
double [] | gamma | ||
) |
The number of points is \(n\), the dimension \(s\), and the \(s\) weight factors are gamma[
\(r\)]
, \(r = 0, 1, …, (s-1)\).
The \(n\) points will be chosen later.
DiscShiftBaker1 | ( | PointSet | set | ) |
Constructor with the point set set
.
All the points are copied in an internal array.
DiscShiftBaker1 | ( | ) |
Empty constructor.
One must set the points, the dimension, and the weight factors before calling any method.
double compute | ( | double | points[][], |
int | n, | ||
int | s | ||
) |
Computes the discrepancy ( baker1 ) for the \(s\)-dimensional points of set points
, containing \(n\) points.
All weights \(\gamma_r = 1\).