SSJ
V. 2.6.

## umontreal.iro.lecuyer.probdist Class KolmogorovSmirnovDistQuick

```java.lang.Object
umontreal.iro.lecuyer.probdist.ContinuousDistribution
umontreal.iro.lecuyer.probdist.KolmogorovSmirnovDist
umontreal.iro.lecuyer.probdist.KolmogorovSmirnovDistQuick
```
All Implemented Interfaces:
Distribution

`public class KolmogorovSmirnovDistQuickextends KolmogorovSmirnovDist`

Extends the class `KolmogorovSmirnovDist` for the distribution. The methods of this class are much faster than those of class `KolmogorovSmirnovDist`.

Field Summary

Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
`decPrec`

Constructor Summary
`KolmogorovSmirnovDistQuick(int n)`
Constructs a distribution with parameter n.

Method Summary
` double` `barF(double x)`
Returns the complementary distribution function.
`static double` ```barF(int n, double x)```
Computes the complementary distribution P[Dn >= x] with parameter n, in a form that is more precise in the upper tail, using the program described in.
` double` `cdf(double x)`
Returns the distribution function F(x).
`static double` ```cdf(int n, double x)```
Computes the distribution function u = P[Dn <= x] with parameter n, using the program described in.
` double` `density(double x)`
Returns f (x), the density evaluated at x.
`static double` ```density(int n, double x)```
Computes the density for the distribution with parameter n.
` double` `inverseF(double u)`
Returns the inverse distribution function x = F-1(u).
`static double` ```inverseF(int n, double u)```
Computes the inverse x = F-1(u) of the distribution F(x) with parameter n.

Methods inherited from class umontreal.iro.lecuyer.probdist.KolmogorovSmirnovDist
`getN, getParams, setN, toString`

Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
`getMean, getStandardDeviation, getVariance, getXinf, getXsup, inverseBisection, inverseBrent, setXinf, setXsup`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Constructor Detail

### KolmogorovSmirnovDistQuick

`public KolmogorovSmirnovDistQuick(int n)`
Constructs a distribution with parameter n.

Method Detail

### density

`public double density(double x)`
Description copied from class: `ContinuousDistribution`
Returns f (x), the density evaluated at x.

Overrides:
`density` in class `KolmogorovSmirnovDist`
Parameters:
`x` - value at which the density is evaluated
Returns:
density function evaluated at x

### cdf

`public double cdf(double x)`
Description copied from interface: `Distribution`
Returns the distribution function F(x).

Specified by:
`cdf` in interface `Distribution`
Overrides:
`cdf` in class `KolmogorovSmirnovDist`
Parameters:
`x` - value at which the distribution function is evaluated
Returns:
distribution function evaluated at x

### barF

`public double barF(double x)`
Description copied from class: `ContinuousDistribution`
Returns the complementary distribution function. The default implementation computes bar(F)(x) = 1 - F(x).

Specified by:
`barF` in interface `Distribution`
Overrides:
`barF` in class `KolmogorovSmirnovDist`
Parameters:
`x` - value at which the complementary distribution function is evaluated
Returns:
complementary distribution function evaluated at x

### inverseF

`public double inverseF(double u)`
Description copied from class: `ContinuousDistribution`
Returns the inverse distribution function x = F-1(u). Restrictions: u∈[0, 1].

Specified by:
`inverseF` in interface `Distribution`
Overrides:
`inverseF` in class `KolmogorovSmirnovDist`
Parameters:
`u` - value at which the inverse distribution function is evaluated
Returns:
the inverse distribution function evaluated at u

### density

```public static double density(int n,
double x)```
Computes the density for the distribution with parameter n.

### cdf

```public static double cdf(int n,
double x)```
Computes the distribution function u = P[Dn <= x] with parameter n, using the program described in. This method uses Pomeranz's recursion algorithm and the Durbin matrix algorithm for n <= 500, which returns at least 13 decimal digits of precision. It uses the Pelz-Good asymptotic expansion in the central part of the range for n > 500 and returns at least 7 decimal digits of precision everywhere for 500 < n <= 100000. For n > 100000, it returns at least 5 decimal digits of precision for all u > 10-16, and a few correct decimals when u <= 10-16. This method is much faster than method cdf of `KolmogorovSmirnovDist` for moderate or large n. Restriction: n >= 1.

### barF

```public static double barF(int n,
double x)```
Computes the complementary distribution P[Dn >= x] with parameter n, in a form that is more precise in the upper tail, using the program described in. It returns at least 10 decimal digits of precision everywhere for all n <= 500, at least 6 decimal digits of precision for 500 < n <= 200000, and a few correct decimal digits (1 to 5) for n > 200000. This method is much faster and more precise for x close to 1, than method barF of `KolmogorovSmirnovDist` for moderate or large n. Restriction: n >= 1.

### inverseF

```public static double inverseF(int n,
double u)```
Computes the inverse x = F-1(u) of the distribution F(x) with parameter n.

SSJ
V. 2.6.

To submit a bug or ask questions, send an e-mail to Pierre L'Ecuyer.