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中位数回归模型线性性的自适应速率最优检验AI 解读

This article is concerned with testing the hypothesis that a conditional median function is linear against a nonparametric alternative with unknown smoothness. We develop a test that is uniformly consistent against alternatives whose distance from the linear model converges to zero at the fastest possible rate. The test does not require knowledge of the distribution of the model's random noise component, and it permits conditional heteroscedasticity of unknown form. The…

蒙特卡洛计算中的动态加权重要性抽样AI 解读

This article describes a new Monte Carlo algorithm, dynamically weighted importance sampling (DWIS), for simulation and optimization. In DWIS, the state of the Markov chain is augmented to a population. At each iteration, the population is subject to two move steps, dynamic weighting and population control. These steps ensure that DWIS can move across energy barriers like dynamic weighting, but with the weights well controlled and with a finite expectation. The estimates can…

不变性、可识别性与形态测量AI 解读

The form of an object is that characteristic that remains invariant under a group of transformations comprising translation, rotation, and possibly reflection. Group invariance thus naturally plays an important role in the statistical analysis of forms. We examine the existing methods for the statistical analysis of form from the invariance perspective. We begin with a review of the important basic ideas behind invariance and derive a maximal invariant under the group of…

马尔可夫链边际自助法AI 解读

Markov chain marginal bootstrap (MCMB) is a new method for constructing confidence intervals or regions for maximum likelihood estimators of certain parametric models and for a wide class of M estimators of linear regression. The MCMB method distinguishes itself from the usual bootstrap methods in two important aspects: it involves solving only one-dimensional equations for parameters of any dimension and produces a Markov chain rather than a (conditionally) independent…

平滑器与 Cp、广义最大似然及扩展指数准则AI 解读

Nonparametric regression, often called smoothing, is a widely used data analysis method. The use of a smoother requires the choice of a smoothing parameter that by balancing fidelity and roughness controls how much smoothing is done. Two popular selection criteria for choosing the smoothing parameter are Cp and generalized maximum likelihood (GML). Each of these has its own problems. ForCp, the problem is its high variability, whereas for GML, the problem is its potentially…

利用降维识别大规模时间序列集合中的共享成分AI 解读

In this article we present a framework for parsimonious modeling of large ensembles of time series. The idea is to identify a small number of stochastic time series components such that each series in the ensemble is a weighted sum of series-specific realizations of the components. We present an estimation procedure that is computationally tractable for large datasets. Through simulations, we argue that the estimators perform well. We illustrate the method using two…

室内环境源邻近效应的带标记点过程模型AI 解读

In indoor air quality studies, discrepancies between personal and stationary indoor air quality monitors arise because of the source proximity effect, in which pollutant sources near the respondent cause elevated and highly variable exposures. In a set of experiments in a home, concentrations of a continuously emitting tracer gas were simultaneously monitored at different distances from the tracer gas source. Concentration time series are modeled at collinear monitoring…

联合分析模型的统一方法AI 解读

We present a unified approach to conjoint analysis models using a Bayesian framework. One data source is used to form a prior distribution for the partworths, whereas full-profile evaluations under a rating scale, ranking, discrete choice, or constant-sum scale constitute the likelihood data (“one model fits all”). Standard existing models for conjoint analysis, considered in the literature, become particular cases of the proposed specification, and explicit formulas for the…

解释黑人与白人的财富差距AI 解读

Many applications involve a decomposition of the mean intergroup difference in a given variable into the portion attributable to differences in the distribution of one or more explanatory variables and that due to differences in the conditional expectation function. This article notes two interrelated reasons why the Blinder–Oaxaca (B–O) method—the approach most commonly used in the literature—may yield misleading results. We suggest a natural solution that both provides a…

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三步删失分位数回归与婚外情应用AI 解读

This article suggests very simple three-step estimators for censored quantile regression models with a separation restriction on the censoring probability. The estimators are theoretically attractive (i.e., asymptotically as efficient as the celebrated Powell's censored least absolute deviation estimator). At the same time, they are conceptually simple and have trivial computational expenses. They are especially useful in samples of small size or models with many regressors,…

统计遗传学非参数原假设检验中的群体异质性与单倍型频率误设调整AI 解读

Population heterogeneity and misspecified population haplotype frequencies are potential sources of bias in a variety of hypothesis testing problems in statistical genetics. Several strategies have been proposed for adjusting for population heterogeneity, but the theoretical basis for the strategies has been developed in relatively narrow contexts, and the methods in general do not exploit all of the available information. Here a generally applicable approach for efficient…

复杂抽样调查数据的潜类别分析AI 解读

High fruit and vegetable intake is associated with decreased cancer risk. However, dietary recall data from national surveys suggest that, on any given day, intake falls below the recommended minima of three daily servings of vegetables and two daily servings of fruit. There is no single widely accepted measure of “usual” intake. One approach is to regard the distribution of intake as a mixture of “regular” (relatively frequent) and “nonregular” (relatively infrequent)…

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用于时间序列拟合不足诊断的综合检验AI 解读

A new portmanteau test for time series, more powerful than the tests of Ljung and Box and Monti, is proposed. The test is based on the mth root of the determinant of the mth autocorrelation matrix. It is shown that the proposed statistic is a function of all of the squared multiple correlation coefficients of the regressions of the residuals on their lags when the number of lags goes from 1 to m. It can also be written as a function of the first m partial autocorrelation…

估计重复事件过程的期望总事件数AI 解读

We consider estimation of the cumulative mean function of a process recurring in time, such as the numbers of arrests or migrations accrued by an individual, as a function of their age. We call this theage profile of a series of events. In some situations we can expect a finite value for the total number of events experienced by an individual, for example, when the distribution of the interevent times is improper, so that the process may cease at a finite time with positive…

Cox回归中缺失协变量的双半参数方法AI 解读

The problem of nuisance covariate model specification is considered in Cox regression where the maximum semiparametric likelihood method is used to handle the missing covariates. A component of the covariates is modeled nonparametrically to achieve robustness against covariate model misspecification and to reduce the number of possibly intractable integrations involved in the parametric modeling of the covariates. The statistical properties of the proposed method are…

一种精确的多元模型结构分解AI 解读

We propose a simple and structured procedure for decomposing a vector of time series into trend, cycle, seasonal, and irregular components. Contrary to common practice, we do not assume these components to be orthogonal conditional on their past. However, the state–space representation employed ensures that their estimates converge to values with null variances and covariances. Null variances are very important, as they ensure that the components do not change when the…

观测误差下的变点、边界与前沿估计AI 解读

A range of problems in economics and statistics involve calculation of the boundary, or frontier, of the support of a distribution. Several practical and attractive solutions exist if the sampled distribution has a sharp discontinuity at the frontier, but accuracy can be greatly diminished if the data are observed with error. Indeed, if the error is additive and has variance σ2 then inaccuracies are usually of order σ, for small σ. In this article we suggest an elementary…

聚类失效时间数据的半参数混合效应模型AI 解读

The Cox proportional hazards model with a random effect has been proposed for the analysis of data which consist of a large number of small clusters of correlated failure time observations. The class of linear transformation models provides many useful alternatives to the Cox model for analyzing univariate failure time data. In this article, we generalize these models by incorporating random effects, which generate the dependence among the failure times within the cluster,…