MNO-PQRS: Max Nonnegativity Ordering-Piecewise-Quadratic Rate Smoothing

被引:14
作者
Chen, Huifen [1 ]
Schmeiser, Bruce W. [2 ]
机构
[1] Chung Yuan Christian Univ, Dept Ind & Syst Engn, Taoyuan, Taiwan
[2] Purdue Univ, Sch Ind Engn, W Lafayette, IN 47907 USA
来源
ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION | 2017年 / 27卷 / 03期
关键词
I-SMOOTH; nonhomogeneous Poisson process; piecewise-constant rate functions; piecewise linear; random variates; system simulation; CUMULATIVE INTENSITY FUNCTION; NONPARAMETRIC-ESTIMATION; POISSON-PROCESS;
D O I
10.1145/3067663
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In both cyclic and finite-horizon contexts, piecewise-constant rate functions are commonly encountered in models with nonhomogeneous Poisson processes. We develop an algorithm, with no user-specified parameters, that returns a smoother rate function that maintains the expected number of arrivals. The algorithm proceeds in two steps: PQRS (Piecewise-Quadratic Rate Smoothing) returns a continuous and differentiable piecewise-quadratic function without regard to negativity. If negative rates occur, then MNO (Max Nonnegativity Ordering) returns the maximum of zero and another piecewise-quadratic function. MNO maintains continuity of rates and first derivatives, but with some exceptions. Our analysis allows fitting the MNO-PQRS function to require storage complexity of the order of the number of intervals and computational complexity of the order of the number of intervals squared. MNO-PQRS can be used as a stand-alone routine, or as an endgame for the authors' earlier algorithm, I-SMOOTH.
引用
收藏
页数:19
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