论文检索

随机期限下的最优停止及其在随机冻结的完全信息最优选择问题中的应用AI 解读

A general theorem is given showing that an optimal stopping problem with independent random horizon is essentially equivalent to a “discounted” fixed horizon optimal stopping problem derived from it. The result is used to treat the “full information” secretary problem, where a known number of applicants for a job are potentially available. Applicants are interviewed sequentially with no recall, and their X i -values are observed, where the X i are iid random variables from a…

随机期限下的最优停止及随机冻结最佳选择问题AI 解读

A general theorem is given showing that an optimal stopping problem with independent random horizon is essentially equivalent to a “discounted” fixed horizon optimal stopping problem derived from it. The result is used to treat the “full information” secretary problem, where a known number of applicants for a job are potentially available. Applicants are interviewed sequentially with no recall, and their X i -values are observed, where the X i are iid random variables from a…

假设检验中的合理性与无偏性AI 解读

The notion of a “rationality criterion” is defined. This criterion reflects a desirable property for statistical procedures that deal with censored data. In hypothesis testing situations, we show that when adapting this criterion to a uniformly most powerful unbiased (UMPU) test of comparing the scale parameters of two distributions, sometimes it is possible to determine a test so that it is unbiased and sometimes this is impossible. The question thus remains: What is more…

假设检验中的理性准则与无偏性AI 解读

The notion of a “rationality criterion” is defined. This criterion reflects a desirable property for statistical procedures that deal with censored data. In hypothesis testing situations, we show that when adapting this criterion to a uniformly most powerful unbiased (UMPU) test of comparing the scale parameters of two distributions, sometimes it is possible to determine a test so that it is unbiased and sometimes this is impossible. The question thus remains: What is more…

负相依随机变量的最优停止价值比较与先知不等式AI 解读

Let $\mathbf{Y} = (Y_1, \cdots, Y_n)$ be random variables satisfying the weak negative dependence condition: $P(Y_i < a_i\mid Y_1 < a_1, \cdots, Y_{i-1}) \leq P(Y_i < a_i)$ for $i = 2, \cdots, n$ and all constants $a_1, \cdots, a_n$. Let $\mathbf{X} = (X_1, \cdots, X_n)$ have independent components, where $X_i$ and $Y_i$ have the same marginal distribution, $i = 1, \cdots, n$. It is shown that $V(\mathbf{X}) \leq V(\mathbf{Y})$, where $V(\mathbf{Y}) = \sup \{EY_t: t \text{is a stopping rule for} Y_1,\cdots, Y_n\}$…

被选中负指数分布总体的均值估计AI 解读

SUMMARY Let Xi be independent, negative exponentially distributed with unknown expectation λi, i = 1, …, k. Let J and M denote the (random) indices of the maximal and minimal observation, respectively. The paper considers estimation of the random quantities λJ and λM. The loss function is (a – λM)2/λ2 M for λM, and correspondingly for λJ. UMVUE and minimax estimators are shown to exist and are exhibited, and certain other reasonable estimators are discussed.

关于 Fisher 一个公式的注记AI 解读

Fisher gives a formula for computing the asymptotic variance of any function of multinomial variables. It is observed that in full generality this formula is false, but a sufficient condition for its correctness is given, and an alternative formula, which is always correct, is supplied.