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java.lang.Object umontreal.iro.lecuyer.probdist.DiscreteDistributionInt umontreal.iro.lecuyer.probdist.UniformIntDist
public class UniformIntDist
Extends the class DiscreteDistributionInt
for
the discrete uniform distribution over the range [i, j].
Its mass function is given by
Field Summary |
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Fields inherited from class umontreal.iro.lecuyer.probdist.DiscreteDistributionInt |
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EPSILON |
Constructor Summary | |
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UniformIntDist(int i,
int j)
Constructs a discrete uniform distribution over the interval [i, j]. |
Method Summary | |
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double |
barF(int x)
Returns bar(F)(x), the complementary distribution function. |
static double |
barF(int i,
int j,
int x)
Computes the discrete uniform complementary distribution function bar(F)(x). |
double |
cdf(int x)
Returns the distribution function F evaluated at x (see). |
static double |
cdf(int i,
int j,
int x)
Computes the discrete uniform distribution function defined in. |
int |
getI()
Returns the parameter i. |
static UniformIntDist |
getInstanceFromMLE(int[] x,
int n)
Creates a new instance of a discrete uniform distribution over integers with parameters i and j estimated using the maximum likelihood method based on the n observations x[k], k = 0, 1,…, n - 1. |
int |
getJ()
Returns the parameter j. |
double |
getMean()
Returns the mean of the distribution function. |
static double |
getMean(int i,
int j)
Computes and returns the mean E[X] = (i + j)/2 of the discrete uniform distribution. |
static double[] |
getMLE(int[] x,
int n)
Estimates the parameters (i, j) of the uniform distribution over integers using the maximum likelihood method, from the n observations x[k], k = 0, 1,…, n - 1. |
double[] |
getParams()
Return a table containing the parameters of the current distribution. |
double |
getStandardDeviation()
Returns the standard deviation of the distribution function. |
static double |
getStandardDeviation(int i,
int j)
Computes and returns the standard deviation of the discrete uniform distribution. |
double |
getVariance()
Returns the variance of the distribution function. |
static double |
getVariance(int i,
int j)
Computes and returns the variance Var[X] = [(j - i + 1)2 -1]/12 of the discrete uniform distribution. |
static int |
inverseF(int i,
int j,
double u)
Computes the inverse of the discrete uniform distribution function. |
int |
inverseFInt(double u)
Returns the inverse distribution function F-1(u), where 0 <= u <= 1. |
double |
prob(int x)
Returns p(x), the probability of x. |
static double |
prob(int i,
int j,
int x)
Computes the discrete uniform probability p(x). |
void |
setParams(int i,
int j)
Sets the parameters i and j for this object. |
String |
toString()
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Methods inherited from class umontreal.iro.lecuyer.probdist.DiscreteDistributionInt |
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barF, cdf, getXinf, getXsup, inverseF |
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 UniformIntDist(int i, int j)
Method Detail |
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public double prob(int x)
DiscreteDistributionInt
prob
in class DiscreteDistributionInt
x
- value at which the mass function must be evaluated
public double cdf(int x)
DiscreteDistributionInt
cdf
in class DiscreteDistributionInt
x
- value at which the distribution function must be evaluated
public double barF(int x)
DiscreteDistributionInt
barF
in class DiscreteDistributionInt
x
- value at which the complementary distribution function
must be evaluated
public int inverseFInt(double u)
DiscreteDistributionInt
inverseFInt
in class DiscreteDistributionInt
u
- value in the interval (0, 1) for which
the inverse distribution function is evaluated
public double getMean()
Distribution
public double getVariance()
Distribution
public double getStandardDeviation()
Distribution
public static double prob(int i, int j, int x)
public static double cdf(int i, int j, int x)
public static double barF(int i, int j, int x)
public static int inverseF(int i, int j, double u)
public static double[] getMLE(int[] x, int n)
x
- the list of observations used to evaluate parametersn
- the number of observations used to evaluate parameters
public static UniformIntDist getInstanceFromMLE(int[] 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(int i, int j)
public static double getVariance(int i, int j)
public static double getStandardDeviation(int i, int j)
public int getI()
public int getJ()
public void setParams(int i, int j)
public double[] getParams()
public String toString()
toString
in class Object
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