本文整理汇总了Java中org.apache.commons.math3.exception.util.LocalizedFormats.SCALE属性的典型用法代码示例。如果您正苦于以下问题：Java LocalizedFormats.SCALE属性的具体用法？Java LocalizedFormats.SCALE怎么用？Java LocalizedFormats.SCALE使用的例子？那么, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类org.apache.commons.math3.exception.util.LocalizedFormats的用法示例。
在下文中一共展示了LocalizedFormats.SCALE属性的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: ParetoDistribution
/**
* Creates a Pareto distribution.
*
* @param rng Random number generator.
* @param scale Scale parameter of this distribution.
* @param shape Shape parameter of this distribution.
* @param inverseCumAccuracy Inverse cumulative probability accuracy.
* @throws NotStrictlyPositiveException if {@code scale <= 0} or {@code shape <= 0}.
*/
public ParetoDistribution(RandomGenerator rng,
double scale,
double shape,
double inverseCumAccuracy)
throws NotStrictlyPositiveException {
super(rng);
if (scale <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SCALE, scale);
}
if (shape <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SHAPE, shape);
}
this.scale = scale;
this.shape = shape;
this.solverAbsoluteAccuracy = inverseCumAccuracy;
}
示例2: WeibullDistribution
/**
* Creates a Weibull distribution.
*
* @param rng Random number generator.
* @param alpha Shape parameter.
* @param beta Scale parameter.
* @param inverseCumAccuracy Maximum absolute error in inverse
* cumulative probability estimates
* (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
* @throws NotStrictlyPositiveException if {@code alpha <= 0} or {@code beta <= 0}.
* @since 3.1
*/
public WeibullDistribution(RandomGenerator rng,
double alpha,
double beta,
double inverseCumAccuracy)
throws NotStrictlyPositiveException {
super(rng);
if (alpha <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SHAPE,
alpha);
}
if (beta <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SCALE,
beta);
}
scale = beta;
shape = alpha;
solverAbsoluteAccuracy = inverseCumAccuracy;
}
示例3: CauchyDistribution
/**
* Creates a Cauchy distribution.
*
* @param rng Random number generator.
* @param median Median for this distribution.
* @param scale Scale parameter for this distribution.
* @param inverseCumAccuracy Maximum absolute error in inverse
* cumulative probability estimates
* (defaults to {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
* @throws NotStrictlyPositiveException if {@code scale <= 0}.
* @since 3.1
*/
public CauchyDistribution(RandomGenerator rng,
double median,
double scale,
double inverseCumAccuracy) {
super(rng);
if (scale <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SCALE, scale);
}
this.scale = scale;
this.median = median;
solverAbsoluteAccuracy = inverseCumAccuracy;
}
示例4: GammaDistribution
/**
* Creates a Gamma distribution.
*
* @param rng Random number generator.
* @param shape the shape parameter
* @param scale the scale parameter
* @param inverseCumAccuracy the maximum absolute error in inverse
* cumulative probability estimates (defaults to
* {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
* @throws NotStrictlyPositiveException if {@code shape <= 0} or
* {@code scale <= 0}.
* @since 3.1
*/
public GammaDistribution(RandomGenerator rng,
double shape,
double scale,
double inverseCumAccuracy)
throws NotStrictlyPositiveException {
super(rng);
if (shape <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SHAPE, shape);
}
if (scale <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SCALE, scale);
}
this.shape = shape;
this.scale = scale;
this.solverAbsoluteAccuracy = inverseCumAccuracy;
this.shiftedShape = shape + Gamma.LANCZOS_G + 0.5;
final double aux = FastMath.E / (2.0 * FastMath.PI * shiftedShape);
this.densityPrefactor2 = shape * FastMath.sqrt(aux) / Gamma.lanczos(shape);
this.logDensityPrefactor2 = FastMath.log(shape) + 0.5 * FastMath.log(aux) -
FastMath.log(Gamma.lanczos(shape));
this.densityPrefactor1 = this.densityPrefactor2 / scale *
FastMath.pow(shiftedShape, -shape) *
FastMath.exp(shape + Gamma.LANCZOS_G);
this.logDensityPrefactor1 = this.logDensityPrefactor2 - FastMath.log(scale) -
FastMath.log(shiftedShape) * shape +
shape + Gamma.LANCZOS_G;
this.minY = shape + Gamma.LANCZOS_G - FastMath.log(Double.MAX_VALUE);
this.maxLogY = FastMath.log(Double.MAX_VALUE) / (shape - 1.0);
}
示例5: GumbelDistribution
/**
* Build a new instance.
*
* @param rng Random number generator
* @param mu location parameter
* @param beta scale parameter (must be positive)
* @throws NotStrictlyPositiveException if {@code beta <= 0}
*/
public GumbelDistribution(RandomGenerator rng, double mu, double beta) {
super(rng);
if (beta <= 0) {
throw new NotStrictlyPositiveException(LocalizedFormats.SCALE, beta);
}
this.beta = beta;
this.mu = mu;
}