SSJ
3.3.1
Stochastic Simulation in Java
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Extends the class ContinuousDistribution for the inverse gamma distribution with shape parameter \(\alpha> 0\) and scale parameter \(\beta> 0\), also known as the Pearson type V distribution. More...
Public Member Functions | |
InverseGammaDist (double alpha, double beta) | |
Constructs an InverseGammaDist object with parameters \(\alpha\) = alpha and \(\beta\) = beta . | |
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 | getAlpha () |
Returns the \(\alpha\) parameter of this object. | |
double | getBeta () |
Returns the \(\beta\) parameter of this object. | |
void | setParam (double alpha, double beta) |
Sets the parameters \(\alpha\) and \(\beta\) of this object. | |
double [] | getParams () |
Returns a table containing the parameters of the current distribution. More... | |
String | toString () |
Returns a String containing 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 alpha, double beta, double x) |
Computes the density function of the inverse gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\). | |
static double | cdf (double alpha, double beta, double x) |
Computes the cumulative probability function of the inverse gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\). | |
static double | barF (double alpha, double beta, double x) |
Computes the complementary distribution function of the inverse gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\). | |
static double | inverseF (double alpha, double beta, double u) |
Computes the inverse distribution function of the inverse gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\). | |
static double [] | getMLE (double[] x, int n) |
Estimates the parameters \((\alpha,\beta)\) of the inverse gamma distribution using the maximum likelihood method, from the \(n\) observations \(x[i]\), \(i = 0, 1,…, n-1\). More... | |
static InverseGammaDist | getInstanceFromMLE (double[] x, int n) |
Creates a new instance of the inverse gamma distribution with parameters \(\alpha\) and \(\beta\) estimated using the maximum likelihood method based on the \(n\) observations \(x[i]\), \(i = 0, 1, …, n-1\). More... | |
static double | getMean (double alpha, double beta) |
Returns the mean \(E[X] = \beta/ (\alpha- 1)\) of the inverse gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\). | |
static double | getVariance (double alpha, double beta) |
Returns the variance \(\mbox{Var}[X] = \beta^2 / ((\alpha- 1)^2(\alpha- 2))\) of the inverse gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\). | |
static double | getStandardDeviation (double alpha, double beta) |
Returns the standard deviation of the inverse gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\). | |
Protected Attributes | |
double | alpha |
double | beta |
double | logam |
Protected Attributes inherited from ContinuousDistribution | |
double | supportA = Double.NEGATIVE_INFINITY |
double | supportB = Double.POSITIVE_INFINITY |
Additional Inherited Members | |
Public Attributes inherited from ContinuousDistribution | |
int | decPrec = 15 |
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 inverse gamma distribution with shape parameter \(\alpha> 0\) and scale parameter \(\beta> 0\), also known as the Pearson type V distribution.
The density function is given by
\[ f(x) = \left\{\begin{array}{ll} \displaystyle\frac{\beta^{\alpha}e^{-\beta/ x}}{x^{\alpha+ 1} \Gamma(\alpha)} & \quad\mbox{for } x > 0 \\ 0 & \quad\mbox{otherwise,} \end{array} \right. \tag{dinvgam} \]
where \(\Gamma\) is the gamma function. The distribution function is given by
\[ F(x) = 1 - F_G\left(\frac{1}{x}\right) \qquad\mbox{for } x > 0, \tag{Finvgam} \]
and \(F(x) = 0\) otherwise, where \(F_G(x)\) is the distribution function of a gamma distribution with shape parameter \(\alpha\) and scale parameter \(\beta\).
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.
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static |
Creates a new instance of the inverse gamma distribution with parameters \(\alpha\) and \(\beta\) 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 |
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static |
Estimates the parameters \((\alpha,\beta)\) of the inverse gamma 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: [ \(\alpha\), \(\beta\)]. The equations of the maximum likelihood are the same as the equations of the gamma distribution, with the sample \(y_i = 1/x_i\).
x | the list of observations to use to evaluate parameters |
n | the number of observations to use to evaluate parameters |
double [] getParams | ( | ) |
Returns a table containing the parameters of the current distribution.
This table is put in regular order: [ \(\alpha\), \(\beta\)].
Implements Distribution.
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.