Nonparametric estimation of the conditional distribution function in a semiparametric censorship model

In this paper we propose a new nonparametric estimator of the conditional distribution function under a semiparametric censorship model. We establish an asymptotic representation of the estimator as a sum of iid random variables, balanced by some kernel weights. This representation is used for obtaining large sample results such as the rate of uniform convergence of the estimator, or its limit distributional law. We prove that the new estimator outperforms the conditional Kaplan–Meier estimator for censored data, in the sense that it exhibits lower asymptotic variance. Illustration through real data analysis is provided.     

A probablistic analysis for an optimal screening problem

Summary We consider a lotL formed byN apparently similar unitsW ₁,…,W _N, where each of theW _i may come from one of two different populationsP ₁ andP ₂;T ₁,…,T _N denote the corresponding lifetimes. The units fromP _i undergo a failure of kindi and their survival function isS _i (t). We assume that the failure rate function are known and that the units fromP ₁ are ?substandard?: λ ₁ (t)≥λ ₂ (t), ∀t≥0. We want to putW ₁,…,W _N under a pre-operational test (burn-in test) in order to eliminate at least a great part of the substandard units and we face the problem of obtaining a rule for stopping the test under the assumption that, with the failure of a unit, it is possible to recognize the population from which the unit comes. Such a problem will be formalized as an optimal stopping problem for a suitably defined Markov process. Our study shall evidentiate some fundamental aspects of the problem and the role of the prior distribution of the (random) numberM ₀ of those units inL coming fromP ₁ (substandard). The latter distribution has a great influence on the form of the solution. This research was supported by the C.N.R. Project ?Statistica Bayesiana e Simulazione in Affidalità e Modellistica Biologica?.     

Estimation and goodness-of-fit procedures for Farlie–Gumbel–Morgenstern bivariate copula of order statistics

In this study, we provide the Farlie–Gumbel–Morgenstern bivariate copula of rth and sth order statistics. The main emphasis in this study is on the inference procedure which is based on the maximum pseudo-likelihood estimate for the copula parameter. As for the methodology, goodness-of-fit test statistic for copulas which is based on a Cramér–von Mises functional of the empirical copula process is applied for selecting an appropriate model by bootstrapping. An application of the methodology to simulated data set is also presented.     

An omnibus two-sample test for ranked-set sampling data

We develop an omnibus two-sample test for ranked-set sampling (RSS) data. The test statistic is the conditional probability of seeing the observed sequence of ranks in the combined sample, given the observed sequences within the separate samples. We compare the test to existing tests under perfect rankings, finding that it can outperform existing tests in terms of power, particularly when the set size is large. The test does not maintain its level under imperfect rankings. However, one can create a permutation version of the test that is comparable in power to the basic test under perfect rankings and also maintains its level under imperfect rankings. Both tests extend naturally to judgment post-stratification, unbalanced RSS, and even RSS with multiple set sizes. Interestingly, the tests have no simple random sampling analog.     

Identifying Systemically Important Banks: A temporal approach for macroprudential policies

Contrary to the general belief, systemic risk does not only regard the risk posed by balance sheet relationships and interdependencies among institutions. It also features a temporal dimension related to the inappropriate responses of financial market participants to changes in risk over time. This paper proposes a method to simultaneously address the cross-sectional and the time dimension in which systemic risk materializes. The method is based on the TOPHITS algorithm. It provides three scores, namely borrowing, lending and time scores: the first two represent the systemic importance of the borrowing and the lending activity associated with each financial institution,while the third represents an empirical Early Warning Signal of the financial crisis. Our findings reveal that the identification of the time score as an indicator for an incoming market distress could be relevant to design macro prudential policies.     

中国手机媒体发展前景分析

分析了日本I-MODE取得巨大成功的原因和不足之处,指出无论是从技术上还是从企业模式上,手机媒体在中国的发展都不可能直接拷贝I-MODE模式,只能以I-MODE为借鉴。中国电信发展迅速,手机媒体在中国现阶段发展的重点是手机短信,手机短信市场巨大,但在发展中也存在着一些问题,主要有虚假与不良信息传播、侵犯个人隐私、信息垃圾、信息安全等。然而可以预见,随着3G在中国的逐渐普及以及相关法规的完善,手机媒体将实现网络化、宽带化,将带来一个巨大的媒体市场。     

水溶性高聚物萃取光度法测定水中苯胺的研究

利用水溶性高聚物在无机盐存在下可分成两相的特点,实现了碱性条件下,聚乙二醇-4000对水样中的苯胺的定量萃取.在pH=11.5溶液中,苯胺与8-羟基喹啉形成偶氮化合物,应用分光光度法对其含量定量测定(ε=2.4×104L·mol-1·cm-1).该方法快速、简单、无毒、干扰小,苯胺含量在0.12～2.0mg L符合比耳定律,回收率95%～105%,为水样中苯胺的测定提供了一种较好的方法.