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面板计数数据的非参数检验AI 解读

Panel count data arise when a recurrent event is under investigation and each study subject is observed only at discrete time points. In this situation, observed data include only the numbers of occurrences of the event of interest between observation time points and no information is available on subjects between their observation time points. We propose a nonparametric test for comparing the point processes characterising the recurrent event when only panel count data are…

多变量与空间极值的依赖度量：性质与推断AI 解读

We present properties of a dependence measure that arises in the study of extreme values in multivariate and spatial problems. For multivariate problems the dependence measure characterises dependence at the bivariate level, for all pairs and all higher orders up to and including the dimension of the variable. Necessary and sufficient conditions are given for subsets of dependence measures to be self‐consistent, that is to guarantee the existence of a distribution with such…

最近邻分类模型中的似然推断AI 解读

Traditionally the neighbourhood size k in the k‐nearest‐neighbour algorithm is either fixed at the first nearest neighbour or is selected on the basis of a crossvalidation study. In this paper we present an alternative approach that develops the k‐nearest‐neighbour algorithm using likelihood‐based inference. Our method takes the form of a generalised linear regression on a set of k‐nearest‐neighbour autocovariates. By defining the k‐nearest‐neighbour algorithm in this way we…

Fisher 信息为零时的置信区域AI 解读

We examine the asymptotic behaviour of confidence regions in identifiable one‐dimensional parametric models with smooth likelihood function and information equal to zero at a critical point of the parameter space. Confidence regions are based on inversion of the likelihood ratio test statistic and of some common forms of the score and Wald test statistics. For fixed parameter values other than the critical point, all these statistics have limiting x2(1) distributions, but…

考虑个体内相关性的边际非参数核回归AI 解读

There has been substantial recent interest in non‐ and semiparametric methods for longitudinal or clustered data with dependence within clusters. It has been shown rather inexplicably that, when standard kernel smoothing methods are used in a natural way, higher efficiency is obtained by assuming independence than by using the true correlation structure. It is shown here that this result is a natural consequence of how standard kernel methods incorporate the within‐subject…

竞争风险下现状数据的非参数估计AI 解读

A great deal of recent attention has focused on the estimation of survival distributions based on current status data, an extreme form of interval censored data. This particular data structure arises in a wide variety of applications where cross‐sectional observation either naturally occurs or is preferred to more traditional forms of follow‐up. Here we consider current status data in the context of competing risks. We briefly consider simple parametric models as a backdrop…

基于不完美诊断检验的失效时间分布估计AI 解读

Sequentially‐administered diagnostic tests used to determine the occurrence of a silent event are sometimes subject to error, leading to false positive and false negative test results. In such cases, standard methods for interval censored data do not give valid estimates of the distribution of the time to the event. We present methods for estimating the distribution of the time to the event that account for multiple types of imperfect diagnostic test, as well as differing…

随机效应 Cox 模型的泊松建模方法AI 解读

We propose a Poisson modelling approach to nested random effects Cox proportional hazards models. An important feature of this approach is that the principal results depend only on the first and second moments of the unobserved random effects. The orthodox best linear unbiased predictor approach to random effects Poisson modelling techniques enables us to justify appropriate consistency and optimality. The explicit expressions for the random effects given by our approach…

利用匹配先验实现频率学派推断AI 解读

Nuisance parameters do not pose any problems in Bayesian inference as marginalisation allows for study of the posterior distribution solely in terms of the parameter of interest. However, no general solution is available for removing nuisance parameters under the frequentist paradigm. In this paper, we merge the two approaches to construct a general procedure for frequentist elimination of nuisance parameters through the use of matching priors. In particular, we perform…

利用逆向三阶矩估计中心子空间AI 解读

Modern graphical tools have enhanced our ability to learn many things from data directly. In recent years, dimension reduction has proven to be an effective tool for generating low‐dimensional summary plots without appreciable loss of information. Some well‐known inverse regression methods for dimension reduction such as sliced inverse regression (Li, 1991) and sliced average variance estimation (Cook & Weisberg, 1991) have been developed to estimate summary plots for…

非线性混合效应模型中的非参数估计AI 解读

A nonparametric approach is developed herein to estimate parameters in nonlinear mixed effects models. Asymptotic properties of the nonparametric maximum likelihood estimators and associated computational algorithms are provided. Empirical Bayes estimators of functionals of the random effects are also developed. Applications to population pharmacokinetics are given.

关于部分经验似然的一则说明AI 解读

A partial profile empirical likelihood for a semiparametric mixture model (Zou et al., 2002) is shown to originate in a conditional likelihood involving additional nuisance parameters. The partial likelihood is the conditional likelihood with the nuisance parameters replaced by their estimators from the full likelihood. The conditional likelihood suggests alternative estimators. We demonstrate that the partial likelihood estimator is more efficient than an estimator for…

von Mises–Fisher 分布的改进似然比检验AI 解读

Explicit expressions for the directed likelihood statistic, r, and two modified directed likelihood statistics, r* and r†, are given for several standard hypotheses on concentrations in von Mises–Fisher distributions, and for several standard hypotheses on mean directions in von Mises distributions.

具有潜在治疗生效滞后时间的加性风险模型AI 解读

In many clinical trials for evaluating treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical treatment procedure or chemical compound would be in full effect. In this paper, semiparametric regression models are proposed and studied for estimating the treatment effect accounting for such latent lag times. The new models take advantage of the invariant property of the additive hazards model in marginalising over an…

协变量缺失的匹配病例对照研究中的半参数推断AI 解读

We consider the problem of matched studies with a binary outcome that are analysed using conditional logistic regression, and for which data on some covariates are missing for some study participants. Methods for this problem involve either modelling the distribution of missing covariates or modelling the probability of data being missing. For this second approach, the previously proposed method did not make use of data for those persons with missing covariate data except in…

共同主成分模型中的影响函数与离群点检测：稳健方法AI 解读

The common principal components model for several groups of multivariate observations assumes equal principal axes but different variances along these axes among the groups. Influence functions for plug‐in and projection‐pursuit estimates under a common principal component model are obtained. Asymptotic variances are derived from them. Outlier detection is possible using partial influence functions.

一种实用的仿射等变多元中位数AI 解读

A robust affine equivariant estimator of location for multivariate data is proposed which becomes the univariate median for data of dimension one. The estimator is robust in the sense that it has a bounded influence function, a positive breakdown value and has high efficiency compared to the sample mean for heavy‐tailed distributions. Perhaps its greatest strength is that, unlike other affine equivariant multivariate medians, it is easily computed for data in any practical…

非平稳空间协方差结构的估计AI 解读

We introduce a method for estimating nonstationary spatial covariance structure from space‐time data and apply the method to an analysis of Sydney wind patterns. Our method constructs a process honouring a given spatial covariance matrix at observing stations and uses one or more stationary processes to describe conditional behaviour given observing site values. The stationary processes give a localised description of the spatial covariance structure. The method is…

存在异质性时非参数捕获—再捕获模型的新贝叶斯方法AI 解读

The intrinsic heterogeneity of individuals is a potential source of bias in estimation procedures for capture‐recapture models. To account for this heterogeneity in the model a hierarchical structure has been proposed whereby the probabilities that each animal is caught on a single occasion are modelled as independent draws from a common unknown distribution F. However, there is general agreement that modelling F by a simple parametric curve may lead to unsatisfactory…

多层捕获—再捕获数据的贝叶斯模型判别AI 解读

Extending the work of Dupuis (1995), we motivate a range of biologically plausible models for multiple‐site capture‐recapture and show how the original Gibbs sampling algorithm of Dupuis can be extended to obtain posterior model probabilities using reversible jump Markov chain Monte Carlo. This model selection procedure improves upon previous analyses in two distinct ways. First, Bayesian model averaging provides a robust parameter estimation technique which properly…

再生模拟在马尔可夫链蒙特卡洛中的适用性AI 解读

We consider the central limit theorem and the calculation of asymptotic standard errors for the ergodic averages constructed in Markov chain Monte Carlo. Chan & Geyer (1994) established a central limit theorem for ergodic averages by assuming that the underlying Markov chain is geometrically ergodic and that a simple moment condition is satisfied. While it is relatively straightforward to check Chan & Geyer's conditions, their theorem does not lead to a consistent and easily…

前向搜索中的附加变量t检验与被掩盖异常值对模型选择的影响AI 解读

Monitoring the t‐tests for individual regression coefficients in ‘forward’ search fails to identify the importance of observations to the significance of the individual regressors. This failure is due to the ordering of the data by the search. We introduce an added‐variable test which has the desired properties since the projection leading to residuals destroys the effect of the ordering. An example illustrates the effect of several masked outliers on model selection.…

作为平滑器的鞍点近似AI 解读

This note investigates the sense in which saddlepoint approximations act as smoothers of discrete distributions. The discrete problem is embedded in a continuous model that closely matches it on the discrete sample space, with saddlepoint approximation yielding an inference that is almost exact for the continuous model. The same applies to conditional distributions. An example is given and implications for inference are discussed.

纵向数据估计方程方法中可忽略缺失的检验AI 解读

We address the matter of determining whether or not missing data in longitudinal studies are ignorable with regard to quasilikelihood or estimating equations approaches. This involves testing for whether or not the zero‐mean property of estimating equations holds true. Chen & Little (1999) proposed testing for significant differences among parameter estimators calculated from sample subsets with different patterns of missing data, whereas we propose a more unified…