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区间删失模型与寿命分布的模拟推断AI 解读

Interval-censored lifetime data arise when individuals in a study are inspected intermittently so that a lifetime is observed to lie between two successive times. In settings where only these two times are available, methods exist for nonparametric or parametric estimation of lifetime distributions. However, there has been virtually no discussion of how inspection processes may be estimated or identified. Such estimates are needed if one is to generate interval-censored data…

频率学派预测区间与预测分布AI 解读

We consider parametric frameworks for the prediction of future values of a random variable Y, based on previously observed data X. Simple pivotal methods for obtaining calibrated prediction intervals are presented and illustrated. Frequentist predictive distributions are defined as confidence distributions, and their utility is demonstrated. A simple pivotal-based approach that produces prediction intervals and predictive distributions with well-calibrated frequentist…

回归中响应选择与缺失数据问题的半参数方法AI 解读

Summary Suppose that data are generated according to the model f(y|x; θ) g(x), where y is a response and x are covariates. We derive and compare semiparametric likelihood and pseudolikelihood methods for estimating θ for situations in which units generated are not fully observed and in which it is impossible or undesirable to model the covariate distribution. The probability that a unit is fully observed may depend on y, and there may be a subset of covariates which is…

基于回顾性发现机制的推断：输血相关艾滋病数据分析AI 解读

In some epidemiologic studies, identification of individuals for study is dependent on the occurrence of some event. Once an individual is identified, the time of a previous event, termed an initiating event, is determined retrospectively. This article considers problems of estimation when initiating events occur as a nonhomogeneous Poisson process, and the time s from the initiating event to the final event has pdf f(s) independent of the time of the initiating event. A…

泊松回归模型中过度离散的检测检验AI 解读

Poisson regression models are widely used in analyzing count data. This article develops tests for detecting extra-Poisson variation in such situations. The tests can be obtained as score tests against arbitrary mixed Poisson alternatives and are generalizations of tests of Fisher (1950) and Collings and Margolin (1985). Accurate approximations for computing significance levels are given, and the power of the tests against negative binomial alternatives is compared with…

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位置—尺度模型中回归系数估计的一致性与效率AI 解读

The effect on estimation of regression coefficients in linear location-scale models is investigated when the error distribution is misspecified. It is shown that the maximum likelihood estimator under the incorrect model is still consistent. Its asymptotic efficiency relative to that of the maximum likelihood estimator based on the correct model is obtained and the estimation of asymptotic variances for the regression coefficient estimators is addressed.

泊松过程数据的回归方法AI 解读

This article is directed toward situations where individuals can experience repeated events, and data on an individual consist of the number and occurrence times of events, along with concomitant variables. Methods of regression analysis are presented, based on Poisson process and proportional intensity assumptions. These include parametric and semi-parametric approaches to model fitting, model assessment, and the treatment of random effects. In addition, insight is gained…

寿命回归模型的一则注记AI 解读

Lifetime regression models that are additive in some transform of either the survivor function or quantile function are considered. Graphical assessment and connections between the two families are discussed.

寿命回归模型札记AI 解读

Lifetime regression models that are additive in some transform of either the survivor function or quantile function are considered. Graphical assessment and connections between the two families are discussed.

Markov 假设下面板数据的分析AI 解读

Methods for the analysis of panel data under a continuous-time Markov model are proposed. We present procedures for obtaining maximum likelihood estimates and associated asymptotic covariance matrices for transition intensity parameters in time homogeneous models, and for other process characteristics such as mean sojourn times and equilibrium distributions. Generalizations to handle covariance analysis and to the fitting of certain nonhomogeneous models are presented, and…

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广义岭估计量的均方误差性质AI 解读

Mean squared errors are derived and examined for a number of generalized ridge (GR) regression estimators, and the estimators are compared in a number of specific regression models. The potential of GR estimators is discussed.

极值分布与Weibull分布参数置信区间的近似AI 解读

Approximations are introduced for the distributions of a number of pivotal quantities used in estimation and testing procedures for the extreme value and Weibull distributions. The approximations are accurate even for small sample sizes, and allow the determination of percentage points for distributions which until now were approachable only via Monte Carlo methods.

极值与Weibull分布参数置信区间的近似AI 解读

Approximations are introduced for the distributions of a number of pivotal quantities used in estimation and testing procedures for the extreme value and Weibull distributions. The approximations are accurate even for small sample sizes, and allow the determination of percentage points for distributions which until now were approachable only via Monte Carlo methods.

Weibull 分布参数的条件与无条件置信区间AI 解读

Analogous conditional and unconditional confidence interval procedures for the two parameter Weibull distribution are discussed. Results of an empirical study are given which suggest that, in many practical situations, the two procedures considered lead to near-equivalent results. Ramifications of the empirical results are also considered.

摘要暂缺

柯西与逻辑斯蒂分布位置、尺度参数的条件置信区间AI 解读

Conditional confidence interval estimation procedures for the location and scale parameters of the Cauchy and logistic distributions are discussed. There are two aims: The first is to discuss computational aspects of using the conditional confidence interval approach, and the second is to give a rough numerical comparison of the conditional confidence interval procedures and the unconditional confidence interval procedures for the parameters of the Cauchy and logistic…