归功于
发表于 2025-3-28 17:37:53
Central Limit Theorems for Cluster Point Processes,ce of independent and identically distributed (i.i.d.) point processes .. on ... Each point mass . in . is replaced by an independent copy of . centered at .. If . is a Poisson process, the resulting point process . is said to be a Poisson cluster point process (Poisson C.P.P.).
朴素
发表于 2025-3-28 18:50:37
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喧闹
发表于 2025-3-29 00:13:48
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彩色的蜡笔
发表于 2025-3-29 07:09:08
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deactivate
发表于 2025-3-29 09:57:28
Ideas from the Foundations of Sampling Applied to the One-way Layout, with two treatments and no technical error. Basic considerations concerning the role and choice of randomization are shown to correspond. There is no obvious value in the design context for analogues of πps sampling. An optimality result for estimation of the difference in treatment effect is given.
陈腐思想
发表于 2025-3-29 13:04:04
Analytic Uses of Survey Data: A Review,rom the point of view of estimation as well as for performing hypothesis tests and developing confidence intervals. Many problems such as analysis of linear models and log-linear models have been studied recently. We cite the main results. Estimation of population percentiles is also discussed.
Mundane
发表于 2025-3-29 16:46:16
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Acclaim
发表于 2025-3-29 21:50:22
Contemporary Irish Poetry and the Canonov chain (with .(0) = 1). For any given . > 0, put p(.) = .. How small is m = inf{.(.): . ≤ .}? In other words, what pairs (.) can occur?.The problem remains unsolved but substantial contributions to the eventual solution have been made by V. M. Joshi. This paper reviews Joshi’s work and outlines the current state of play.
Peculate
发表于 2025-3-30 01:40:15
Contemporary Irish Poetry and the Canonby probabilists. This paper reviews applications of probability to such problems as reciprocity failure, granularity, and adjacency effects in photographic materials, concentrating on developments since 1971.
战胜
发表于 2025-3-30 07:49:20
Contemporary Irish Republican Prison WritingHere {..}.. is an independent and identically distributed sequence of non-negative random variables and {..}.. is a Markov chain, with stationary transition probabilities, independent of {..}.∞. In this paper we are concerned with the limiting distributions of the maximum term X. = sup... and of the sum S. = X. +… + X..