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脑电轨迹的评估与比较：非平稳时间序列中的潜在结构AI 解读

We explore and illustrate the use of time series decomposition methods for evaluating and comparing latent structure in nonstationary electroencephalographic (EEG) traces obtained from depressed patients during brain seizures induced as part of electroconvulsive therapy (ECT). Analysis of the patterns of change over time in the frequency structure of such EEG data provides insight into the neurophysiological mechanisms of action of this effective but poorly understood…

零售客户层面的贸易促销建模：约束参数层级模型应用AI 解读

We consider the problem of utilizing data at the retail/market level on sales and marketing mix variables to help manufacturers optimize the allocation of trade promotional budgets across areas. Major consumer packaged goods manufacturers budget at least one-half of their total marketing expenses to trade promotions. Trade promotional deals are designed to encourage retailers to promote products by temporarily reducing the price, putting them in in-store displays, or…

用广义断点回归设计评估加州囚犯分类制度AI 解读

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

不同类别子群间部分测量潜在特质的比较AI 解读

This article presents a method for estimating the subgroup distributions of a latent trait measured as a normal variate in the population. This problem occurs in large-scale assessments, such as the National Assessment of Educational Progress, the National Adult Literacy Survey, and other programs where proficiencies are estimated via marginal maximum likelihood through a model based on item-response theory. Heretofore, estimates of subgroup means were often estimated using…

流行病学分型数据建模与疾病传播的似然推断AI 解读

A model for epidemiologic typing data is introduced, and likelihood ratio methods are developed for evaluating these data as evidence about disease spread. The observed data consist of microorganism subtypes from an index case of infectious disease, cases clustered with the index case, and a reference sample. The likelihood methods are evaluated via probabilities of observing epidemiologic subtypes that represent strong and sometimes misleading evidence favoring one…

多准则决策合并：原住民捕鲸管理程序的竞争性开发AI 解读

International Whaling Commission management of aboriginal subsistence whaling will eventually use an aboriginal whaling management procedure (AWMP) chosen from a collection of candidate procedures after grueling simulation testing. An AWMP is a fully automatic algorithm designed to operate on the results of an assessment (i.e., a statistical estimation problem relying on sparse series of whale abundance data) to produce a catch limit in each year of real or simulated…

发育毒理学中多元结局的伪似然建模AI 解读

The primary goal of this article is to determine benchmark doses based on the ethylene glycol study, which comprises data from a developmental toxicity study in mice. Because the data involve a vector of malformation indicators, a flexible model for multivariate clustered data is required. An exponential family model is considered and pseudolikelihood-based inferential tools are proposed, hence avoiding excessive computational requirements.

合并 PCR DNA 分型实验数据：精子分型的应用AI 解读

The polymerase chain reaction (PCR) is a procedure by which the DNA in a single cell can be made to replicate many times in a test tube. By amplifying the DNA from individual sperm cells and typing the results, estimates of male recombination fractions can be made, which are valuable for creating genetic maps and locating regions of unusually intense crossover activity on the human genome. Because PCR typing results are subject to random error, stochastic models must be…

有序响应变化的非参数两样本比较AI 解读

We discuss two-armed clinical trials in which an ordinal response is observed on entry and at follow-up. In certain subject areas, such data are often reduced to the counts of patients who have deteriorated, remained the same, or improved. We develop asymptotic distribution theory to compare this approach to the use of nonparametric tests based on poststratification of the follow-up responses according to the entry levels. The theory for the latter approach is established by…

k 均值与修剪 k 均值的稳健性性质AI 解读

The generalized k means method is based on the minimization of the discrepancy between a random variable (or a sample of this random variable) and a set with k points measured through a penalty function Φ. As in the M estimators setting (k = 1), a penalty function, Φ, with unbounded derivative, Ψ, naturally leads to nonrobust generalized k means. However, surprisingly the lack of robustness extends also to the case of bounded Ψ; that is, generalized k means do not inherit…

多元异常值识别规则的掩蔽崩溃点AI 解读

In this article, we consider simultaneous outlier identification rules for multivariate data, generalizing the concept of so-called α outlier identifiers, as presented by Davies and Gather for the case of univariate samples. Such multivariate outlier identifiers are based on estimators of location and covariance. Therefore, it seems reasonable that characteristics of the estimators influence the behavior of outlier identifiers. Several authors mentioned that using estimators…

泊松过程的贝叶斯多尺度模型AI 解读

I introduce a class of Bayesian multiscale models (BMSM's) for one-dimensional inhomogeneous Poisson processes. The focus is on estimating the (discretized) intensity function underlying the process. Unlike the usual transform-based approach at the heart of most wavelet-based methods for Gaussian data, these BMSM's are constructed using recursive dyadic partitions (RDP's) within an entirely likelihood-based framework. Each RDP may be associated with a binary tree, and a new…

含治愈比例生存数据的新贝叶斯模型AI 解读

We consider Bayesian methods for right-censored survival data for populations with a surviving (cure) fraction. We propose a model that is quite different from the standard mixture model for cure rates. We provide a natural motivation and interpretation of the model and derive several novel properties of it. First, we show that the model has a proportional hazards structure, with the covariates depending naturally on the cure rate. Second, we derive several properties of the…

协变量缺失下的比例风险回归AI 解读

Nonparametric maximum likelihood (NPML) is used to estimate regression parameters in a proportional hazards regression model with missing covariates. The NPML estimator is shown to be consistent and asymptotically normally distributed under some conditions. EM type algorithms are applied to solve the maximization problem. Variance estimates of the regression parameters are obtained by a profile likelihood approach that uses EM-aided numerical differentiation. Simulation…

依赖删失重复测量下治疗差异的秩估计AI 解读

In comparing the effectiveness of two treatments, suppose that for each patient repeated measurements of an outcome variable are taken at prespecified time points, but some observations may be missing due to the patient's dependent right censoring. In this article, a simple rank estimation procedure, constructed based on an artificial censoring technique, is proposed for the treatment differences over time without imposing a parametric structure on the dependence between the…

参数函数的拟合检验AI 解读

General methods for testing the fit of a parametric function are proposed. The idea underlying each method is to “accept” the prescribed parametric model if and only if it is chosen by a model selection criterion. Several different selection criteria are considered, including one based on a modified version of the Akaike information criterion and others based on various score statistics. The tests have a connection with nonparametric smoothing because they use orthogonal…

单整过程的线性与对数变换检验AI 解读

This article proposes nonnested tests of linear and logarithmic transformations of integrated processes against each other, where the innovations of both series follow autoregressive processes. It is shown that the null distributions of the test statistics for both the linear and logarithmic transformations are nonstandard when the processes have no drift, whereas they are asymptotically normal when the processes have positive drift. Monte Carlo experiments and illustrative…

全局最大值的检验AI 解读

We give simple necessary and sufficient conditions for consistency and asymptotic optimality of a root to the likelihood equation. Based on the results, a large-sample test is proposed for detecting whether a given root is consistent and asymptotically efficient, a property often possessed by the global maximizer of the likelihood function. A number of examples, and the connection between the proposed test and the test of White for model misspecification, are discussed.…

随机筛似然与一般回归模型AI 解读

Consider a semiparametric regression model Y = f(θ, X, ϵ), where f is a known function, θ is an unknown vector, ϵ consists of a random error and possibly of some unobserved variables, and the distribution F(·) of (ϵ, X) is unspecified. This article introduces, in a general setting, new methodology for estimating θ and F(·). The proposed method constructs a profile likelihood defined on random-level sets (a random sieve). The proposed method is related to empirical likelihood…

双重截断数据的非参数方法AI 解读

Truncated data play an important role in the statistical analysis of astronomical observations as well as in survival analysis. The motivating example for this article concerns a set of measurements on quasars in which there is double truncation. That is, the quasars are observed only if their luminosity occurs within a certain finite interval, bounded at both ends, with the interval varying for different observations. Nonparametric methods for the testing and estimation of…

利用数据驱动先验进行加性非参数回归的变量选择与函数估计AI 解读

A hierarchical Bayesian approach is proposed for variable selection and function estimation in additive nonparametric Gaussian regression models and additive nonparametric binary regression models. The prior for each component function is an integrated Wiener process resulting in a posterior mean estimate that is a cubic smoothing spline. Each of the explanatory variables is allowed to be in or out of the model, and the regression functions are estimated by model averaging.…

用自回归负多项回归模型分析多种情绪的时间变化AI 解读

This article presents an autoregressive random coefficient model with overdispersed negative multinomial marginal distributions for the analysis of heterogeneity and serial dependencies in multivariate longitudinal count data. The model structure consists of four components that take into account (a) individual difference effects, (b) random time effects, (c) multiple event categories, and (d) autodependencies. The last component is based on a stochastic integer-valued…

用信号提取方法建模具有脉冲与变化基线的激素时间序列AI 解读

Hormones serve as regulating signals for many biological processes. In recent years, it was determined that many hormones are secreted in a pulsatile manner and that the pulsatile secretion pattern, in addition to the absolute concentration level, is important in regulating biological processes. Consequently, it is necessary to characterize the latent secretion patterns from measurements of concentration levels. The characterization is complicated by the presence of a…

时变暴露对重复二元结局边际均值的因果效应估计AI 解读

We provide sufficient conditions for estimating from longitudinal data the causal effect of a time-dependent exposure or treatment on the marginal probability of response for a dichotomous outcome. We then show how one can estimate this effect under these conditions using the g-computation algorithm of Robins. We also derive the conditions under which some current approaches to the analysis of longitudinal data, such as the generalized estimating equations (GEE) approach of…