Stable and invariant adjusted profile likelihood and directed likelihood for curved exponential models

For curved exponential models, the modified profile likelihoodand the modified directed likelihood are approximated, witherror 0(n^-1) under ordinary repeated sampling, by explicitlydefined and invariant quantities which do not require specificationof an ancillary and which are stable in the sense of havingthe appropriate conditionality property with respect to anyreasonable ancillary.     

A note on profile likelihood for exponential tilt mixture models

Suppose that independent observations are drawn from multipledistributions, each of which is a mixture of two component distributionssuch that their log density ratio satisfies a linear model witha slope parameter and an intercept parameter. Inference forsuch models has been studied using empirical likelihood, andmixed results have been obtained. The profile empirical likelihoodof the slope and intercept has an irregularity at the null hypothesisso that the two component distributions are equal. We derivea profile empirical likelihood and maximum likelihood estimatorof the slope alone, and obtain the usual asymptotic propertiesfor the estimator and the likelihood ratio statistic regardlessof the null. Furthermore, we show the maximum likelihood estimatorof the slope and intercept jointly is consistent and asymptoticallynormal regardless of the null. At the null, the joint maximumlikelihood estimator falls along a straight line through theorigin with perfect correlation asymptotically to the firstorder.     

Integrated likelihood functions for non-Bayesian inference

Consider a model with parameter = (, ), where is the parameterof interest, and let L(, ) denote the likelihood function. Oneapproach to likelihood inference for is to use an integratedlikelihood function, in which is eliminated from L(, ) by integratingwith respect to a density function (|). The goal of this paperis to consider the problem of selecting (|) so that the resultingintegrated likelihood function is useful for non-Bayesian likelihoodinference. The desirable properties of an integrated likelihoodfunction are analyzed and these suggest that (|) should be chosenby finding a nuisance parameter that is unrelated to and thentaking the prior density for to be independent of . Such anunrelated parameter is constructed and the resulting integratedlikelihood is shown to be closely related to the modified profilelikelihood.     

最大似然法和贝叶斯推论与似然比检验探讨泽泻目系统发育关系

应用最大似然法(ML)、贝叶斯推论(BI)、邻接法(NJ)和似然比检验(hLRTs)进行泽泻目分子系统学研究。所用的rbcL基因序列代表了泽泻目14科46属以及作为外类群的6相关属。研究结果表明,*等级制似然比检验表明泽泻目rbcL序列最适合的DNA进化模型为GTR+I+G,最大似然法、贝叶斯法和邻接法构建的系统发育树拓扑结构相似,没有显著的差异,但贝叶斯树支持率较高;泽泻目为一单系类群,由两个主要谱系分支构成,深层分布格局由5个主要分支构成。基于分子系统发育树,文中对泽泻目科间、水鳖科+茨藻科、泽泻科+花蔺科+黄花蔺科、和"Cymodoeaceae complex"的系统发育关系进行了讨论。研究结果还表明,泽泻目系统发育关系可能还需要更多的证据进一步的澄清。