Algorithm 1006

Rémy Abergel, L. Moisan
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引用次数: 3

Abstract

We present a computational procedure to evaluate the integral ∫yx sp-1 e-μs ds for 0 ≤ x < y ≤ +∞,μ = ±1, p> 0, which generalizes the lower (x=0) and upper (y=+∞) incomplete gamma functions. To allow for large values of x, y, and p while avoiding under/overflow issues in the standard double precision floating point arithmetic, we use an explicit normalization that is much more efficient than the classical ratio with the complete gamma function. The generalized incomplete gamma function is estimated with continued fractions, with integrations by parts, or, when x ≈ y, with the Romberg numerical integration algorithm. We show that the accuracy reached by our algorithm improves a recent state-of-the-art method by two orders of magnitude, and it is essentially optimal considering the limitations imposed by floating point arithmetic. Moreover, the admissible parameter range of our algorithm (0 ≤ p,x,y ≤ 1015) is much larger than competing algorithms, and its robustness is assessed through massive usage in an image processing application.
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算法1006
给出了积分∫yx sp-1 e-μs ds在0≤x < y≤+∞,μ =±1,p> 0时的计算方法,推广了下(x=0)和上(y=+∞)不完全函数。为了允许x, y和p的大值,同时避免标准双精度浮点运算中的不足/溢出问题,我们使用显式规范化,它比具有完整gamma函数的经典比率更有效。广义不完全函数用连分式估计,用分部积分估计,或者当x≈y时,用Romberg数值积分算法估计。我们表明,我们的算法所达到的精度将最近最先进的方法提高了两个数量级,并且考虑到浮点算法所施加的限制,它本质上是最优的。此外,我们的算法的允许参数范围(0≤p,x,y≤1015)比竞争算法大得多,并且通过在图像处理应用中的大量使用来评估其鲁棒性。
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