public class WeibullDistributionImpl extends AbstractContinuousDistribution implements WeibullDistribution, java.io.Serializable
WeibullDistribution.| Modifier and Type | Field and Description |
|---|---|
static double |
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Default inverse cumulative probability accuracy
|
| Constructor and Description |
|---|
WeibullDistributionImpl(double alpha,
double beta)
Creates weibull distribution with the given shape and scale and a
location equal to zero.
|
WeibullDistributionImpl(double alpha,
double beta,
double inverseCumAccuracy)
Creates weibull distribution with the given shape, scale and inverse
cumulative probability accuracy and a location equal to zero.
|
| Modifier and Type | Method and Description |
|---|---|
double |
cumulativeProbability(double x)
For this distribution, X, this method returns P(X <
x). |
double |
density(double x)
Returns the probability density for a particular point.
|
double |
getNumericalMean()
Returns the mean of the distribution.
|
double |
getNumericalVariance()
Returns the variance of the distribution.
|
double |
getScale()
Access the scale parameter.
|
double |
getShape()
Access the shape parameter.
|
double |
getSupportLowerBound()
Returns the lower bound of the support for the distribution.
|
double |
getSupportUpperBound()
Returns the upper bound of the support for the distribution.
|
double |
inverseCumulativeProbability(double p)
For this distribution, X, this method returns the critical point x, such
that P(X < x) =
p. |
void |
setScale(double beta)
Deprecated.
as of 2.1 (class will become immutable in 3.0)
|
void |
setShape(double alpha)
Deprecated.
as of 2.1 (class will become immutable in 3.0)
|
reseedRandomGenerator, sample, samplecumulativeProbabilityequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcumulativeProbabilitypublic static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
public WeibullDistributionImpl(double alpha,
double beta)
alpha - the shape parameter.beta - the scale parameter.public WeibullDistributionImpl(double alpha,
double beta,
double inverseCumAccuracy)
alpha - the shape parameter.beta - the scale parameter.inverseCumAccuracy - the maximum absolute error in inverse cumulative probability estimates
(defaults to DEFAULT_INVERSE_ABSOLUTE_ACCURACY)public double cumulativeProbability(double x)
x).cumulativeProbability in interface Distributionx - the value at which the CDF is evaluated.x.public double getShape()
getShape in interface WeibullDistributionpublic double getScale()
getScale in interface WeibullDistributionpublic double density(double x)
density in class AbstractContinuousDistributionx - The point at which the density should be computed.public double inverseCumulativeProbability(double p)
p.
Returns Double.NEGATIVE_INFINITY for p=0 and
Double.POSITIVE_INFINITY for p=1.
inverseCumulativeProbability in interface ContinuousDistributioninverseCumulativeProbability in class AbstractContinuousDistributionp - the desired probabilitypjava.lang.IllegalArgumentException - if p is not a valid
probability.@Deprecated public void setShape(double alpha)
setShape in interface WeibullDistributionalpha - the new shape parameter value.@Deprecated public void setScale(double beta)
setScale in interface WeibullDistributionbeta - the new scale parameter value.public double getSupportLowerBound()
public double getSupportUpperBound()
public double getNumericalMean()
public double getNumericalVariance()
TDistributionImpl) or
Double.NaN if it's not definedCopyright © 2010 - 2023 Adobe. All Rights Reserved