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Nonparametric maximum likelihood computation of a U-shaped hazard function

机译:U形危险函数的非参数最大似然计算

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A new algorithm is presented and studied in this paper for fast computation of the nonparametric maximum likelihood estimate of a U-shaped hazard function. It successfully overcomes a difficulty when computing a U-shaped hazard function, which is only properly defined by knowing its anti-mode, and the anti-mode itself has to be found during the computation. Specifically, the new algorithm maintains the constant hazard segment, regardless of its length being zero or positive. The length varies naturally, according to what mass values are allocated to their associated knots after each updating. Being an appropriate extension of the constrained Newton method, the new algorithm also inherits its advantage of fast convergence, as demonstrated by some real-world data examples. The algorithm works not only for exact observations, but also for purely interval-censored data, and for data mixed with exact and interval-censored observations.
机译:提出并研究了一种新的算法,用于快速计算U型危险函数的非参数最大似然估计。它成功地克服了在计算U形危险函数时遇到的困难,该函数只能通过了解其反模来正确定义,并且必须在计算过程中找到反模本身。具体而言,无论新算法的长度为零还是正,它都将保持恒定的危害区间。长度自然地变化,这取决于每次更新后将哪些质量值分配给它们的相关结。作为约束牛顿法的适当扩展,新算法还继承了其快速收敛的优势,如一些实际数据示例所示。该算法不仅适用于精确的观测值,而且还适用于纯间隔检查的数据,以及与精确和间隔检查的观测值混合的数据。

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