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非参数加性回归中的重要变量搜索AI 解读

Nonparametric additive regression is studied under the assumption that only a subset of nonparametric components is nonzero. Each of these nonzero components depends on its own particular explanatory variable, called a significant variable. The search problem for significant variables is considered and an algorithm is proposed which guarantees exponentially decreasing error probabilities as the sample size grows. We show that it is reasonable to use a rough bin estimator…

已知连接函数的加性回归模型估计AI 解读

We consider estimation of an additive nonparametric regression model with known link function. The asymptotic distribution of this regression estimate is given. The practical performance is investigated via an application to the study of migration between East and West Germany.

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双变量生存函数的非参数估计及母婴传播艾滋病应用AI 解读

In this paper we propose a nonparametric estimator of the bivariate survival function when the two durations are subject to right censoring. We consider the situation where the duration variables are successive and are always observed in a particular order, and the censoring mechanism bears on their sum, rather than on each separately. Thus, is they are correlated, the second duration is right censored by a dependent variable. A nonparametric maximum likelihood estimator is…

重复测量中有序组效应的检验AI 解读

In the repeated measures experiment, testing procedures for ordered group effects are proposed using the likelihood ratio principle. The constrained maximum likelihood estimators of ordered group effects are approximated by the isotonic regression of the unconstrained maximum likelihood estimators. Based on these constrained maximum likelihood estimators, test statistics are constructed and are used for detecting ordered group effects. The limiting distributions of the…

有限总体分布函数的一种新估计量AI 解读

In this paper we propose a new estimator for the finite population distribution function when there is auxiliary information available about the population. The new estimator has a smaller asymptotic mean squared error than two leading estimators in the literature. In fact, it is in an optimised form in terms of mean squared error. Results are reported for simulation studies on real and artificial populations.

两个协方差平稳时间序列的独立性检验AI 解读

A one-sided asymptotically normal test for independence between two stationary time series is proposed by first prewhitening the two time series and then basing the test on the residual cross-correlation function. The test statistic is a properly standardised version of the sum of weighted squares of residual cross-correlations, with weights depending on a kernel function. Haugh's (1976) test can be viewed as a special case of our approach in the sense that it corresponds to…

典型变量分析的替代置信区域AI 解读

Recent papers have questioned the appropriateness of the circular confidence regions often drawn around group mean points in canonical variate analysis and proposed improved elliptical regions. This paper develops new theoretical and bootstrap regions of an alternative type, with those constructed using parametric bootstrapping being shown by simulation to perform consistently well.

The problem of estimating the number of binary responses that can be attributed to high levels of a continuous covariate is studied. The distribution of the covariate in the population is combined with the relative odds of response to produce a function, areas under which represent numbers of responses attributable to covariate values in that range. A combination of parametric and nonparametric smoothing is proposed. Consistent estimates of variance are developed as well as…

失效时间变量间依赖强度的评估AI 解读

The correlation p between cumulative hazard variates is considered as a measure of dependence between pairs of failure time variates. Such correlation is readily estimated in the absence of censorship, but modelling assumptions are required for its estimation in the presence of independent right censorship. A semiparametric class of bivariate failure time models, in which a dependence parameter is in one-to-one correspondence with the cumulative hazard variate correlation p,…

捕获率可变的连续时间捕获—再捕获实验推断AI 解读

A two-step procedure based on a partial likelihood is proposed to estimate the size of a closed population for multiple recapture studies in continuous time when the capture rates are permitted to depend on covariates associated with individuals. The asymptotic and small-sample properties of the resulting estimators are investigated.

区间删失数据分布函数非参数极大似然估计札记AI 解读

Gentleman & Geyer (1994) discuss the analysis of interval censored data and present results based on standard convex optimisation theory. Here, this problem is viewed from the perspective of a mixing problem of indicator functions. Using an analogy with the problem of mixture distributions a variety of results are easily derived, including a characterisation theorem for the maximum likelihood estimator and various reliably convergent algorithms. Software for the analysis of…

非线性混合效应模型中使用Laplace近似的一则说明AI 解读

The asymptotic properties of estimates obtained using Laplace's approximation for nonlinear mixed-effects models are investigated. Unlike the restricted maximum likelihood approach, e. g. Wolfinger (1993), here the Laplace approximation is appiled only to the random effects of the integrated likelihood. This results in approximate maximum likelihood estimation. The resulting estimates are shown to be consistent with the rate of convergence depending on both the number of…

二元混合效应模型中的估计效率AI 解读

We investigate the efficiency of likelihood methods for estimating the regression parameters of mixed-effects logistic regression models. One approach uses a conditional likelihood which eliminates the random intercept terms. A second uses the likelihood generated from the marginal distribution of the data where the random intercepts are integrated out. Parametric estimates result from assuming a parametric form for the intercept distribution, whereas we obtain…

二元时间序列互谱的自动估计AI 解读

The penalised Whittle likelihood has recently been shown to have good properties in nonparametric estimation of spectral density functions. This paper extends the approach to the estimation of the cross-spectrum of a bivariate time series. One major difference from the univariate case is that the cross-spectrum estimate is not constrained to be positive, but must result in a positive definite spectral density matrix. An efficient computational method based on iterative…

有限总体累积分布函数估计的模拟外推去卷积AI 解读

We study estimation of a finite population cumulative distribution function when sample units are measured with error. We propose a simple, bias-adjusted estimator that eliminates much of the bias induced by measurement error. A variance estimator for the proposed cumulative distribution function estimator is also obtained.

模型误设下连续再评估方法的一致性AI 解读

This paper studies large sample behaviour of the continual reassessment method used to determine the target dose levels in phase I clinical trials. A sequential maximum likelihood procedure is investigated for local estimation of a given targeted toxicity level. Consistency and asymptotic normality for the maximum likelihood estimates are established under model misspecification and it is shown that, in general, the recommended dose level will converge to the target level.…

生存状态确认存在延迟时的生存分布估计AI 解读

During the interim stages of most large scale clinical trials, knowledge that a patient is alive or dead is usually not up to date. This is due to the pattern of patient visits to hospitals, as well as the administrative set-up used by the study to obtain the information on vital status. If the process of ascertaining vital status is not completely random, then the usual method of estimating the survival curve based on the Kaplan-Meier estimator may be biased. For this…

区间删失数据比例风险模型的秩推断AI 解读

A marginal likelihood approach to fitting the proportional hazards model to interval censored or grouped data is proposed; this approach maximises a likelihood that is the sum over all rankings of the data that are consistent with the observed censoring intervals. As in the usual proportional hazards model, the method does not require specification of the bascline hazard function. The score equations determining the maximum marginal likelihood estimator can be written as the…

系统发育树的自助法：大偏差与离散程度效应AI 解读

A large deviation result is established for the bootstrap empirical distribution in a finite sample space, thereby validating both nonparametric and parametric bootstrapping in certain phylogenetic inference problems. The bias previously observed in the bootstrap distribution of the estimated tree topology is shown to stem from dispersion effects in the joint distribution of sample and bootstrap empirical distributions. Both results are examined for maximum likelihood…

预测分布的渐近性质AI 解读

Second-order asymptotic theory of predictive distributions is investigated. It is shown that estimative distributions with asymptotically efficient estimators can be improved to predictive distributions that do not belong to the model. The model is assumed to be a multidimensional curved exponential family. Predictive distributions can be constructed by shifting estimative distributions in a direction orthogonal to the model. The average Kullback-Leibler divergence from the…

广义线性模型的近似贝叶斯因子与模型不确定性处理AI 解读

Ways of obtaining approximate Bayes factors for generalised linear models are described, based on the Laplace method for integrals. We propose a new approximation which uses only the output of standard computer programs for estimating generalised linear models, this appears to be quite accurate. A reference set of proper priors is suggested, both to represent the situation where there is not much prior information, and to assess the sensitivity of the results to the prior…

一组筛查程序最优排序的贝叶斯模型AI 解读

Bergman & Gittins (1985) propose a screen design problem in which a collection of screens for therapeutic activity and toxicity of pharmaceutical compounds is to be sequenced. They describe conditions under which a natural ordering heuristic based on failure probability per unit cost for each screen is optimal. We propose a Bayesian model in which measures of activity and toxicity are given a joint prior density. The above conditions for optimality are satisfied for this…

杂录：用修正估计方程校正回归中的测量误差AI 解读

A modified estimating equation approach is proposed to correct for measurement error in regression problems. We allow changing measurement error variances and covariances across units, allow the regressors to be fixed, allow estimation of the measurement error variances/covariances and account for uncertainty arising from this estimation, and explicitly model measurement error in the response. Multiple linear, quadratic, Poisson, and logistic regression are considered in…