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java.lang.Object umontreal.iro.lecuyer.probdist.ContinuousDistribution umontreal.iro.lecuyer.probdist.UniformDist
public class UniformDist
Extends the class ContinuousDistribution
for
the uniform distribution
over the interval [a, b].
Its density is
Field Summary |
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Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution |
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decPrec |
Constructor Summary | |
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UniformDist()
Constructs a uniform distribution over the interval (a, b) = (0, 1). |
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UniformDist(double a,
double b)
Constructs a uniform distribution over the interval (a, b). |
Method Summary | |
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double |
barF(double x)
Returns the complementary distribution function. |
static double |
barF(double a,
double b,
double x)
Computes the uniform complementary distribution function bar(F)(x). |
double |
cdf(double x)
Returns the distribution function F(x). |
static double |
cdf(double a,
double b,
double x)
Computes the uniform distribution function as in. |
double |
density(double x)
Returns f (x), the density evaluated at x. |
static double |
density(double a,
double b,
double x)
Computes the uniform density function f (x). |
double |
getA()
Returns the parameter a. |
double |
getB()
Returns the parameter b. |
static UniformDist |
getInstanceFromMLE(double[] x,
int n)
Creates a new instance of a uniform distribution with parameters a and b estimated using the maximum likelihood method based on the n observations x[i], i = 0, 1,…, n - 1. |
double |
getMean()
Returns the mean. |
static double |
getMean(double a,
double b)
Computes and returns the mean E[X] = (a + b)/2 of the uniform distribution with parameters a and b. |
static double[] |
getMLE(double[] x,
int n)
Estimates the parameter (a, b) of the uniform distribution using the maximum likelihood method, from the n observations x[i], i = 0, 1,…, n - 1. |
double[] |
getParams()
Return a table containing the parameters of the current distribution. |
double |
getStandardDeviation()
Returns the standard deviation. |
static double |
getStandardDeviation(double a,
double b)
Computes and returns the standard deviation of the uniform distribution with parameters a and b. |
double |
getVariance()
Returns the variance. |
static double |
getVariance(double a,
double b)
Computes and returns the variance Var[X] = (b - a)2/12 of the uniform distribution with parameters a and b. |
double |
inverseF(double u)
Returns the inverse distribution function x = F-1(u). |
static double |
inverseF(double a,
double b,
double u)
Computes the inverse of the uniform distribution function. |
void |
setParams(double a,
double b)
Sets the parameters a and b for this object. |
String |
toString()
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Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution |
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getXinf, getXsup, inverseBisection, inverseBrent, setXinf, setXsup |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public UniformDist()
public UniformDist(double a, double b)
Method Detail |
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public double density(double x)
ContinuousDistribution
density
in class ContinuousDistribution
x
- value at which the density is evaluated
public double cdf(double x)
Distribution
x
- value at which the distribution function is evaluated
public double barF(double x)
ContinuousDistribution
barF
in interface Distribution
barF
in class ContinuousDistribution
x
- value at which the complementary distribution function is evaluated
public double inverseF(double u)
ContinuousDistribution
inverseF
in interface Distribution
inverseF
in class ContinuousDistribution
u
- value at which the inverse distribution function is evaluated
public double getMean()
ContinuousDistribution
getMean
in interface Distribution
getMean
in class ContinuousDistribution
public double getVariance()
ContinuousDistribution
getVariance
in interface Distribution
getVariance
in class ContinuousDistribution
public double getStandardDeviation()
ContinuousDistribution
getStandardDeviation
in interface Distribution
getStandardDeviation
in class ContinuousDistribution
public static double density(double a, double b, double x)
public static double cdf(double a, double b, double x)
public static double barF(double a, double b, double x)
public static double inverseF(double a, double b, double u)
public static double[] getMLE(double[] x, int n)
x
- the list of observations used to evaluate parametersn
- the number of observations used to evaluate parameters
public static UniformDist getInstanceFromMLE(double[] x, int n)
x
- the list of observations to use to evaluate parametersn
- the number of observations to use to evaluate parameterspublic static double getMean(double a, double b)
public static double getVariance(double a, double b)
public static double getStandardDeviation(double a, double b)
public double getA()
public double getB()
public void setParams(double a, double b)
public double[] getParams()
public String toString()
toString
in class Object
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