An Orthogonality‐Based Estimation of Moments for Linear Mixed Models

Abstract. Estimating higher‐order moments, particularly fourth‐order moments in linear mixed models is an important, but difficult issue. In this article, an orthogonality‐based estimation of moments is proposed. Under only moment conditions, this method can easily be used to estimate the model parameters and moments, particularly those of higher order than the second order, and in the estimators the random effects and errors do not affect each other. The asymptotic normality of all the estimators is provided. Moreover, the method is readily extended to handle non‐linear, semiparametric and non‐linear models. A simulation study is carried out to examine the performance of the new method.     

An Empirical Likelihood Ratio Test for Normality

The empirical likelihood ratio (ELR) test for the problem of testing for normality is derived in this article. The sampling properties of the ELR test and four other commonly used tests are provided and analyzed using the Monte Carlo simulation technique. The power comparisons against a wide range of alternative distributions show that the ELR test is the most powerful of these tests in certain situations.     

Minimax prediction in finite populations

In this paper, minimax predictors are considered for some population quantities of interest, under some specific superpopulation models. Minimax predictors are derived under a binomial superpopulation model. The well known ratio estimator is shown to be minimax under the usual simple regression normal model. Nonparametric minimax predictors are considered under some models. Some of the predictors considered also shown to be admis s ible.     

Approximate Confidence Limits for the Difference between Parameters of Two Pólya Distributions

The problem of calculating approximate confidence limits for the difference between success probability parameters of two Pólya distributions is solved for the first time. We suggest some new methods for determining these approximate confidence limits and consider their application to special cases: namely for the binomial and hypergeometric distributions. The various approximate confidence limits are evaluated and compared.     

Smoothed estimates for nonlinear time series models with irregular data

Time series data observed at unequal time intervals (irregular data) occur quite often and this usually poses problems in its analysis. A recursive form of the exponentially smoothed estimated is here proposed for a nonlinear model with irregularly observed data and its asymptotic properties are discussed An alternative smoother to that of Wright (1985) is also derived. Numerical comparison is made between the resulting estimates and other smoothed estimates.     

A Non-parametric Test for Generalized First-order Autoregressive Models

We derive a non-parametric test for testing the presence of V(X_i,ε_i) in the non-parametric first-order autoregressive model X_i+1=T(X_i)+V(X_i,ε_i)+U(X_i)ε_i+1, where the function T(x) is assumed known. The test is constructed as a functional of a basic process for which we establish a weak invariance principle, under the null hypothesis and under stationarity and mixing assumptions. Bounds for the local and non-local powers are provided under a condition which ensures that the power tends to one as the sample size tends to infinity.The testing procedure can be applied, e.g. to bilinear models, ARCH models, EXPAR models and to some other uncommon models. Our results confirm the robustness of the test constructed in Ngatchou Wandji (1995) and in Diebolt & Ngatchou Wandji (1995).     

论竞争法中两种限制竞争行为的区别与联系

限购排挤行为,是指公用企业或者其他依法具有独占地位的经营者,为了排挤其他经营者而限定他人购买其指定的经营者的商品的行为。滥用行政权力限制竞争行为,根据《反不正当竞争法》第7条的规定,是指政府及其所属部门滥用行政权力,限定他人购买其指定的经营者的商品,限制其他经营者正当的经营活动,或者限制经营者跨地区、跨部门的交易,干扰、阻碍正常的交易活动的行为。限购排挤行为与滥用行政权力限制竞争行为是两种不同的限制竞争行为。对二者进行合理、有效的规制,是竞争法的重要任务。作者阐明这两种行为的概念、特征、法律规制之必要性,并在此基础上对二者进行比较分析,有助于正确地认识和规制这两种行为。     

Normalité asymptotique d'estimateurs convergents du mode conditionnel

We state sufficient conditions for asymptotic normality of convergent estimates of the conditional mode, irrespective of data dependence, and give an application to α-mixing stationary processes.     

关注"常态"生活的意义——家庭社会学研究的一个新视角初探

本文从日常生活的"常态"概念入手,认为选择这样一个"常态"作为研究对象对研究家庭社会学是十分有意义的.具体地说,我们认为以被访人的生活史为切入点,去挖掘和揭示制度安排中的"盲点",应该成为家庭社会学研究的一个新的视角.     

Conflicting contexts: Midwives’ interpretation of childbirth through photo elicitation

IntroductionThis study seeks to explore midwives’ perceptions about childbirth and in particular their beliefs about normality and risk. In the current climate of increasing interventions during labour, it is important to understand the thought processes that impact on midwifery care in order to examine whether these beliefs influence midwifery clinical decision-making.Method12 Midwives who worked in a variety of metropolitan hospitals in Sydney, Australia were interviewed about how they care for women during labour. The study utilised an inductive qualitative design using photo elicitation during the interview process.ResultsSix themes emerged from the data that clearly indicated midwives felt challenged by working in a system dominated by an obstetric model of care that undermined midwifery autonomy in maintaining normal birth. These themes were: desiring normal, scanning the environment, constructing the context, navigating the way, relinquishing desire and reflecting on reality. Most midwives felt they were unable to practice in the manner they were philosophically aligned to, that is, promoting normal birth, as the medical model restricted their practice.DiscussionThe polarised views of childbirth held by midwives and obstetricians do little to enhance normal birth outcomes. Midwives in this study expressed frustration that they were unable to practice midwifery in a way that reflected their belief in normal birth. This, they cite is a result of the oppressive obstetric model prevalent in maternity care facilities in Sydney and the over use of technological interventions during childbirth.