Berry–Esseen type bounds in heteroscedastic errors-in-variables model

ABSTRACT

Consider the heteroscedastic partially linear errors-in-variables (EV) model y_i = x_iβ + g(t_i) + ε_i, ξ_i = x_i + μ_i (1 ? i ? n), where ε_i = σ_ie_i are random errors with mean zero, σ²_i = f(u_i), (x_i, t_i, u_i) are non random design points, x_i are observed with measurement errors μ_i. When f( · ) is known, we derive the Berry–Esseen type bounds for estimators of β and g( · ) under {e_i,?1 ? i ? n} is a sequence of stationary α-mixing random variables, when f( · ) is unknown, the Berry–Esseen type bounds for estimators of β, g( · ), and f( · ) are discussed under independent errors.     

肠道病毒71型景德镇分离株全基因组序列分析

目的分析2011年景德镇地区重症手足口病患儿标本肠道病毒71型（EV71）分离株2011JDZ35全基因组序列特征。方法采集重症手足口病患儿咽拭子标本,进行病毒分离和逆转录一聚合酶链反应（RT．PCR）扩增分离病毒的全基因组序列,并进行全基因组核苷酸序列测定,参考EV71A、B、C各基因型的参考毒株和国内外分离毒株进行同源性分析并构建系统发生树。结果2011JDZ35株的基因组长度为7406bp,其中包括5’端非编码区（5’UTR）长742bp,病毒基因组编码区（ORF）全长6582bp及3’端非编码区（3’UTR）长82bp。ORF编码含2193个氨基酸残基的多聚蛋白。2011JDZ35株基因组的结构与FY08-C30-P14、EV71／Ningbo．CHN／065／2010、HZ08／Hang-zhou／2008十分接近,整个基因组的核苷酸同源性分别为97．3％,97．3％,97．7％;氨基酸同源性为99．1％,99．2％,99．2％。均属于C4亚型,而与Cox．A16国际标准株G10（U05876）及EWl国际标准株BrCr（U22521）差异较大,核苷酸同源性分别仅为77．5％,80．0％;氨基酸同源性为89．8％,94．8％。结论EWl型病毒2011JDZ35株全基因组的组成和结构符合肠道病毒特征,与其他EV71型病毒具有相同的基因组结构,2011JDZ35株与中国大陆浙江宁波株亲缘关系最近,与阜阳株和杭州株等中国大陆内陆地区分离株较近,而与马来西亚、我国台湾、厦门分离株的差异较为明显,与国际标准株则有较大差异;2011JDZ35株与浙江宁波株具有共同的进化途径,推断2011JDZ35株与浙江宁波株可能共同来源于2008年中国大陆地区流行的Ev7l病毒株同一种系。     

Statistical inference for heteroscedastic semi-varying coefficient EV models

This paper proposes an estimation procedure for a class of semi-varying coefficient regression models when the covariates of the linear part are subject to measurement errors. Initial estimates for the regression and varying coefficients are first constructed by the profile least-squares procedure without input from heteroscedasticity, a bias-corrected kernel estimate for the variance function then is proposed, which in turn is used to define re-weighted bias-corrected estimates of the regression and varying coefficients. Large sample properties of the proposed estimates are thoroughly investigated. The finite-sample performance of the proposed estimates is assessed by an extensive simulation study and an application to the Boston housing data set. The simulation results show that the re-weighted bias-corrected estimates outperform the initial estimates and the naive estimates.