| SSJ
    3.2.1
    Stochastic Simulation in Java | 
Extends the class ContinuousDistribution for the uniform distribution [98] (page 276) over the interval \([a,b]\). More...
| Public Member Functions | |
| UniformDist () | |
| Constructs a uniform distribution over the interval \((a,b) = (0,1)\). | |
| UniformDist (double a, double b) | |
| Constructs a uniform distribution over the interval \((a,b)\). | |
| double | density (double x) | 
| double | cdf (double x) | 
| Returns the distribution function \(F(x)\).  More... | |
| double | barF (double x) | 
| Returns \(\bar{F}(x) = 1 - F(x)\).  More... | |
| double | inverseF (double u) | 
| Returns the inverse distribution function \(F^{-1}(u)\), defined in ( inverseF ).  More... | |
| double | getMean () | 
| Returns the mean of the distribution function. | |
| double | getVariance () | 
| Returns the variance of the distribution function. | |
| double | getStandardDeviation () | 
| Returns the standard deviation of the distribution function. | |
| double | getA () | 
| Returns the parameter \(a\). | |
| double | getB () | 
| Returns the parameter \(b\). | |
| void | setParams (double a, double b) | 
| Sets the parameters \(a\) and \(b\) for this object. | |
| double [] | getParams () | 
| Return a table containing the parameters of the current distribution.  More... | |
| String | toString () | 
| Returns a Stringcontaining information about the current distribution. | |
|  Public Member Functions inherited from ContinuousDistribution | |
| abstract double | density (double x) | 
| Returns \(f(x)\), the density evaluated at \(x\).  More... | |
| double | barF (double x) | 
| Returns the complementary distribution function.  More... | |
| double | inverseBrent (double a, double b, double u, double tol) | 
| Computes the inverse distribution function \(x = F^{-1}(u)\), using the Brent-Dekker method.  More... | |
| double | inverseBisection (double u) | 
| Computes and returns the inverse distribution function \(x = F^{-1}(u)\), using bisection.  More... | |
| double | inverseF (double u) | 
| Returns the inverse distribution function \(x = F^{-1}(u)\).  More... | |
| double | getMean () | 
| Returns the mean.  More... | |
| double | getVariance () | 
| Returns the variance.  More... | |
| double | getStandardDeviation () | 
| Returns the standard deviation.  More... | |
| double | getXinf () | 
| Returns \(x_a\) such that the probability density is 0 everywhere outside the interval \([x_a, x_b]\).  More... | |
| double | getXsup () | 
| Returns \(x_b\) such that the probability density is 0 everywhere outside the interval \([x_a, x_b]\).  More... | |
| void | setXinf (double xa) | 
| Sets the value \(x_a=\) xa, such that the probability density is 0 everywhere outside the interval \([x_a, x_b]\).  More... | |
| void | setXsup (double xb) | 
| Sets the value \(x_b=\) xb, such that the probability density is 0 everywhere outside the interval \([x_a, x_b]\).  More... | |
| Static Public Member Functions | |
| static double | density (double a, double b, double x) | 
| Computes the uniform density function \(f(x)\) in ( funiform ). | |
| static double | cdf (double a, double b, double x) | 
| Computes the uniform distribution function as in ( cdfuniform ). | |
| static double | barF (double a, double b, double x) | 
| Computes the uniform complementary distribution function \(\bar{F}(x)\). | |
| static double | inverseF (double a, double b, double u) | 
| Computes the inverse of the uniform distribution function ( cdinvfuniform ). | |
| 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 \(x[i]\), \(i = 0, 1, …, n-1\).  More... | |
| 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 \(x[i]\), \(i = 0, 1, …, n-1\).  More... | |
| 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 \(b\).  More... | |
| static double | getVariance (double a, double b) | 
| Computes and returns the variance \(\mbox{Var}[X] = (b - a)^2/12\) of the uniform distribution with parameters \(a\) and \(b\).  More... | |
| static double | getStandardDeviation (double a, double b) | 
| Computes and returns the standard deviation of the uniform distribution with parameters \(a\) and \(b\).  More... | |
| Additional Inherited Members | |
|  Public Attributes inherited from ContinuousDistribution | |
| int | decPrec = 15 | 
|  Protected Attributes inherited from ContinuousDistribution | |
| double | supportA = Double.NEGATIVE_INFINITY | 
| double | supportB = Double.POSITIVE_INFINITY | 
|  Static Protected Attributes inherited from ContinuousDistribution | |
| static final double | XBIG = 100.0 | 
| static final double | XBIGM = 1000.0 | 
| static final double [] | EPSARRAY | 
Extends the class ContinuousDistribution for the uniform distribution [98] (page 276) over the interval \([a,b]\).
\[ f(x) = 1/(b-a) \qquad\mbox{ for } a\le x\le b \tag{funiform} \]
and 0 elsewhere. The distribution function is
\[ F(x) = (x-a)/(b-a) \qquad\mbox{ for } a\le x\le b \tag{cdfuniform} \]
\[ F^{-1}(u) = a + (b - a)u \qquad\mbox{for }0 \le u \le1. \tag{cdinvfuniform} \]
| double barF | ( | double | x | ) | 
Returns \(\bar{F}(x) = 1 - F(x)\).
| x | value at which the complementary distribution function is evaluated | 
x Implements Distribution.
| double cdf | ( | double | x | ) | 
Returns the distribution function \(F(x)\).
| x | value at which the distribution function is evaluated | 
x Implements Distribution.
| 
 | static | 
Creates a new instance of a uniform distribution with parameters \(a\) and \(b\) estimated using the maximum likelihood method based on the \(n\) observations \(x[i]\), \(i = 0, 1, …, n-1\).
| x | the list of observations to use to evaluate parameters | 
| n | the number of observations to use to evaluate parameters | 
| 
 | static | 
Computes and returns the mean \(E[X] = (a + b)/2\) of the uniform distribution with parameters \(a\) and \(b\).
| 
 | static | 
Estimates the parameter \((a, b)\) of the uniform distribution using the maximum likelihood method, from the \(n\) observations \(x[i]\), \(i = 0, 1, …, n-1\).
The estimates are returned in a two-element array, in regular order: [ \(a\), \(b\)]. The maximum likelihood estimators are the values \((\hat{a}\), \(\hat{b})\) that satisfy the equations
\begin{align*} \hat{a} & = \min_i \{x_i\} \\ \hat{b} & = \max_i \{x_i\}. \end{align*}
See [116] (page 300).
| x | the list of observations used to evaluate parameters | 
| n | the number of observations used to evaluate parameters | 
| double [] getParams | ( | ) | 
Return a table containing the parameters of the current distribution.
This table is put in regular order: [ \(a\), \(b\)].
Implements Distribution.
| 
 | static | 
Computes and returns the standard deviation of the uniform distribution with parameters \(a\) and \(b\).
| 
 | static | 
Computes and returns the variance \(\mbox{Var}[X] = (b - a)^2/12\) of the uniform distribution with parameters \(a\) and \(b\).
| double inverseF | ( | double | u | ) | 
Returns the inverse distribution function \(F^{-1}(u)\), defined in ( inverseF ).
| u | value in the interval \((0,1)\) for which the inverse distribution function is evaluated | 
u Implements Distribution.
 1.8.14
 1.8.14