org.apache.commons.math3.distribution
KolmogorovSmirnovTest
public class KolmogorovSmirnovDistribution extends Object implements Serializable
Treats the distribution of the twosided P(D_n < d)
where
D_n = sup_x G(x)  G_n (x)
for the theoretical cdf G
and
the empirical cdf G_n
.
This implementation is based on [1] with certain quick decisions for extreme values given in [2].
In short, when wanting to evaluate P(D_n < d)
, the method in [1] is
to write d = (k  h) / n
for positive integer k
and
0 <= h < 1
. Then P(D_n < d) = (n! / n^n) * t_kk
, where
t_kk
is the (k, k)
'th entry in the special matrix
H^n
, i.e. H
to the n
'th power.
References:
Constructor and Description 

KolmogorovSmirnovDistribution(int n)
Deprecated.

Modifier and Type  Method and Description 

double 
cdf(double d)
Deprecated.
Calculates
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above). 
double 
cdf(double d,
boolean exact)
Deprecated.
Calculates
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above). 
double 
cdfExact(double d)
Deprecated.
Calculates
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above). 
public KolmogorovSmirnovDistribution(int n) throws NotStrictlyPositiveException
n
 Number of observationsNotStrictlyPositiveException
 if n <= 0
public double cdf(double d) throws MathArithmeticException
P(D_n < d)
using method described in [1] with quick
decisions for extreme values given in [2] (see above). The result is not
exact as with
cdfExact(double)
because
calculations are based on double
rather than
BigFraction
.d
 statisticP(D_n < d)
MathArithmeticException
 if algorithm fails to convert h
to a BigFraction
in expressing
d
as (k  h) / m
for integer k, m
and
0 <= h < 1
.public double cdfExact(double d) throws MathArithmeticException
P(D_n < d)
using method described in [1] with quick
decisions for extreme values given in [2] (see above). The result is
exact in the sense that BigFraction/BigReal is used everywhere at the
expense of very slow execution time. Almost never choose this in real
applications unless you are very sure; this is almost solely for
verification purposes. Normally, you would choose
cdf(double)
d
 statisticP(D_n < d)
MathArithmeticException
 if algorithm fails to convert h
to a BigFraction
in expressing
d
as (k  h) / m
for integer k, m
and
0 <= h < 1
.public double cdf(double d, boolean exact) throws MathArithmeticException
P(D_n < d)
using method described in [1] with quick
decisions for extreme values given in [2] (see above).d
 statisticexact
 whether the probability should be calculated exact using
BigFraction
everywhere at the
expense of very slow execution time, or if double
should be used
convenient places to gain speed. Almost never choose true
in real
applications unless you are very sure; true
is almost solely for
verification purposes.P(D_n < d)
MathArithmeticException
 if algorithm fails to convert h
to a BigFraction
in expressing
d
as (k  h) / m
for integer k, m
and
0 <= h < 1
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