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概率、随机过程与排队论：计算机性能建模的数学基础AI 解读

There are three types: E -an exercise that requires only algebraic manipulation M -a mathematical derivation is required to do the problem Rthe problem is a research problem.An exercise is distinguished from a derivation in that the answer proceeds directly from material in the text and does not require additional analysis.Research problems differ from derivations in that they require more independent work by the student and may require outside reading.For each type of…

事件史的对数线性模型AI 解读

Introduction Log-Linear Anaylsis Log-Linear Anaylsis with Latent Variables and Missing Data Event History Analysis Event History Analysis with Latent Variables and Missing Data A: Computation of the Log-Linear Parameters When Using the IPF Algorithm B: The Log-Linear Model as One of the Generalized Linear Models C: The Newton-Raphson Algorithm D: The Uni-Dimensional Newton Algorithm E: Likelihood Equations for Modified Path Models F: The Estimation of Conditional…

存在长期存活者的生存分析AI 解读

Formulating Tests for the Presence of Immunes and Sufficient Follow-up. Properties of the Kaplan-Meier Estimator. Nonparametric Estimation and Testing. Parametric Models for Single Samples. The Use of Concomitant Information. Large Sample Properties of Parametric Models: Single Samples. Large-Sample Properties of Parametric Models with Covariates. Further Topics. References. Statistical Tables. Index.

拟似然及其应用：最优参数估计的一般方法AI 解读

The General Framework.- An Alternative Approach: E-Sufficiency.- Asymptotic Confidence Zones of Minimum Size.- Asymptotic Quasi-Likelihood.- Combining Estimating Functions.- Projected Quasi-Likelihood.- Bypassing the Likelihood.- Hypothesis Testing.- Infinite Dimensional Problems.- Miscellaneous Applications.- Consistency and Asymptotic Normality for Estimating Functions.- Complements and Strategies for Application.

混合采样方法综述AI 解读

A composite is formed by collecting multiple sample units and combining them in their entirety or in part, to form a new sample. The sample units that make up the composite may retain their integrity or be homogenized through physical processes such as ball milling, sieving, shaking, or centrifuging. One or more subsequent measurements are taken on the composite and the information on the sample units is lost. This counterintuitive loss of information has fueled opposition…

评估一般回归问题中的线性分量数AI 解读

This article presents a method for testing the dimension of a general regression model without assuming any specific model for the distribution of the regressors. Examples of application and comparisons with existing methods are also studied.

通过再生实现自适应马尔可夫链蒙特卡洛AI 解读

Markov chain Monte Carlo (MCMC) is used for evaluating expectations of functions of interest under a target distribution π. This is done by calculating averages over the sample path of a Markov chain having π as its stationary distribution. For computational efficiency, the Markov chain should be rapidly mixing. This sometimes can be achieved only by careful design of the transition kernel of the chain, on the basis of a detailed preliminary exploratory analysis of π. An…

价格与税制改革的参数和非参数方法AI 解读

In many public policy problems, we need to estimate the way in which policy changes affect people's behavior. In the analysis of tax and subsidy reform—the topic of this article—we need to know how tax-induced price changes affect the amounts that people buy of the taxed goods. We present various economic and statistical approaches to obtaining the required estimates. We consider the standard structural methods in economics, where the behavior and welfare of individual…

未问与未答：多项调查的多重插补AI 解读

We present a method of analyzing a series of independent cross-sectional surveys in which some questions are not answered in some surveys and some respondents do not answer some of the questions posed. The method is also applicable to a single survey in which different questions are asked or different sampling methods are used in different strata or clusters. Our method involves multiply imputing the missing items and questions by adding to existing methods of imputation…

时间序列中的冲击诊断AI 解读

Efficient means of modeling aberrant behavior in times series are developed. Our methods are based on state-space forms and allow test statistics for various interventions to be computed from a single run of the Kalman filter smoother. The approach encompasses existing detection methodologies. Departures commonly observed in practice, such as outlying values, level shifts, and switches, are readily dealt with. New diagnostic statistics are proposed. Implications for…

局部异方差积分下若干差分平稳检验的功效AI 解读

This article considers the power properties of the McCabe and Tremayne (MT) test for the difference stationarity of a time series. The limiting distribution of the MT test is derived under sequences of locally heteroscedastic and locally explosive autoregressive (AR) alternatives. The limiting distribution of Dickey–Fuller (DF) statistics is also considered under a sequence of locally heteroscedastic alternatives. Whereas the MT test possesses asymptotic power against both…

广义线性混合模型中的一致估计量AI 解读

A simple method based on simulated moments is proposed for estimating the fixed-effects and variance components in a generalized linear mixed model (GLMM). It is shown that the method is not only computationally attractive but also leads to consistent estimators. On the other hand, simulation shows that the method can be quite inefficient.

纵向数据的半参数随机混合模型AI 解读

We consider inference for a semiparametric stochastic mixed model for longitudinal data. This model uses parametric fixed effects to represent the covariate effects and an arbitrary smooth function to model the time effect and accounts for the within-subject correlation using random effects and a stationary or nonstationary stochastic process. We derive maximum penalized likelihood estimators of the regression coefficients and the nonparametric function. The resulting…

含时变协变量的现状数据局部有效估计AI 解读

In biostatistical applications, interest often focuses on the estimation of the distribution of a failure time variable T. If one observes only whether or not T exceeds an observed monitoring time C, then the data structure is called current status data, also known as interval-censored data, case I. We extend the data structure by allowing the presence of a possibly time-dependent covariate process which is observed up till the monitoring time C. We follow the approach of…

多元累积分布函数的鞍点近似及其抽样与离群检验应用AI 解读

Four multivariate distributions commonly arise in sampling theory: the multinomial, multivariate hypergeometric, Dirichlet, and multivariate Pólya distributions. Second-order saddlepoint approximations are given for approximating these multivariate cumulative distribution functions (cdf's) in their most general settings. Probabilities of rectangular regions associated with these cdf's are also approximated directly using second-order saddlepoint methods. All the…

回归中遗漏变量与测量误差偏差的校正：铅暴露对智商影响的应用AI 解读

Ordinary least squares (OLS) regression estimates are biased, in general, when relevant variables are omitted from the regression equation or when included variables are measured with error. The errors-in-variables bias can be corrected using auxiliary information about unobservable measurement errors. In this article we demonstrate how auxiliary information can also be used to correct for omitted-variables bias. We illustrate our methods with an application to four…

死刑陪审员的公正性：不同层级与缺失机制下的贝叶斯模型比较AI 解读

Jurors who are opposed to the death penalty are excluded from serving on trials in which the defendant may be sentenced to death. The exclusion of such jurors from death-penalty trials raises some concern about the fairness of these juries in deciding the guilt or innocence of a defendant. This article uses data from a survey of behaviors and beliefs of jurors conducted at the conclusion of non–capital offense trials to study this issue. A Bayesian hierarchical model is…

含间歇观测时变二元协变量的删失生存数据分析AI 解读

In survival analyses that include a time-dependent covariate, the standard partial likelihood approach is often complicated by the fact that the necessary observations of the time-dependent covariate are not always available for the subjects in each risk set. In this article, we consider the situation of a binary time-dependent covariate. We specify a longitudinal model for the binary covariate with missing observations and a proportional hazards model for survival time…

评估癌症流行病学风险因素贡献的新策略：黑色素瘤应用AI 解读

A new stochastic framework is proposed for evaluating the individual and collective impact of cancer risk factors, and is applied to data on the incidence of melanoma. It is demonstrated that the standardized incidence ratio of second primary melanoma can be used to estimate the total coefficient of variation in risk in the population, subject to some simplifying assumptions. The coefficient of variation estimated in this manner thus can be used as a benchmark against which…

插补下分层多阶段调查数据的平衡重复复制AI 解读

Balanced repeated replication (BRR) is a popular method for variance estimation in surveys. The standard BRR method works by first creating a set of “balanced” pseudoreplicated datasets from the original dataset. For a survey estimator θ, the BRR variance estimator is the average of squared deviations θ(r) – θ, where θ(r) is the same as θ but based on the data in the rth pseudoreplicated dataset only. But when there are a large number of imputed missing values…

针对有序备择的多元多样本分位数检验AI 解读

We propose and study a multivariate c-sample rank test for order-restricted alternatives when the underlying distributions have a contaminated component. An example concerning lens opacity in adults is presented. The asymptotic distributions are obtained under local mixture alternatives, and Pitman efficiencies are calculated. An empirical power study is also included.