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协方差结构误设下的重复测量分析AI 解读

Summary In recent years various sophisticated methods have been developed for the analysis of repeated measures, or longitudinal data. The more traditional approach, based on a normal likelihood function, has been shown to be unsatisfactory, in the sense of yielding asymptotically biased estimates when the covariance structure is misspecified. More recent methodology, based on generalized linear models and quasi-likelihood estimation, has gained widespread acceptance as…

基于极端值的参数生存模型检验AI 解读

SUMMARY Hougaard proposed a scaled, exponentially tilted, positive stable distribution for the frailty in survival analysis. This leads to a class of survivor functions which encompasses certain special cases. Some tests based on extreme sample values are proposed for assessing the fit of these submodels within a full model. The tests are applied to some data on the breaking strengths of carbon fibres.

重复测量广义线性模型中工作相关矩阵的使用问题AI 解读

In a seminal paper Liang & Zeger (1986) extended the use of generalised linear models to repeated measures data. They based the analysis on specifications for the means and variances of the observations, as usual for generalised linear models, but showed how specifications for the correlations between measurements made on the same unit could be avoided by using a ‘working’ correlation matrix. In some cases the parameters involved in this matrix are subject to an uncertainty…

重复测量广义线性模型中工作相关矩阵的使用问题AI 解读

In a seminal paper Liang & Zeger (1986) extended the use of generalised linear models to repeated measures data. They based the analysis on specifications for the means and variances of the observations, as usual for generalised linear models, but showed how specifications for the correlations between measurements made on the same unit could be avoided by using a ‘working’ correlation matrix. In some cases the parameters involved in this matrix are subject to an uncertainty…

修正 Weibull 模型中的若干非正则检验AI 解读

Certain tests on the parameters of a modified Weibull distribution are considered. Nonregular asymptotic behaviour of likelihood-based test statistics is observed. Competing tests, based on extreme order statistics, are investigated and comparisons are made of power functions.

修正 Weibull 模型中的若干非正则检验AI 解读

Certain tests on the parameters of a modified Weibull distribution are considered. Nonregular asymptotic behaviour of likelihood-based test statistics is observed. Competing tests, based on extreme order statistics, are investigated and comparisons are made of power functions.

与 Weibull 分布相联系的一类多元分布AI 解读

SUMMARY A simple form of multivariate distribution is defined which, for certain parameter values, has Weibull marginals. The distribution has a single parameter governing association between the variates, which may be positive, negative or zero. The simple forms for marginal and conditional distributions, hazard functions and densities make it attractive for practical application and interpretation.

二元二项分布的贝叶斯推断AI 解读

A bivariate distribution is investigated in connection with an application in microbiology. It has binomial marginal and conditional distributions. The parameter structure is examined, and it is shown that a conjugate Bayesian prior distribution arises from prior independence specifications. Under these specifications the usual limiting conjugate prior can be obtained via invariance considerations.

二元二项分布的贝叶斯推断AI 解读

A bivariate distribution is investigated in connection with an application in microbiology. It has binomial marginal and conditional distributions. The parameter structure is examined, and it is shown that a conjugate Bayesian prior distribution arises from prior independence specifications. Under these specifications the usual limiting conjugate prior can be obtained via invariance considerations.

估计方程所得估计量的一致性与不一致性AI 解读

The primary concern is to establish a fairly general framework in which estimators resulting from estimating equations g nθ = 0 are not consistent. This leads on to consistency by an intuitive route. Asymptotic distributions of consistent estimators are also touched upon, and the results are applied to various examples.