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以标准误作为多边价格指数的权重AI 解读

Various multilateral methods for computing price indexes use bilateral comparisons as their basic building blocks. Some give greater weight to those bilateral comparisons deemed more reliable. However, none of the existing reliability measures adjusts for gaps in the data. We show how the standard errors on bilateral price indexes derived using weighted least squares provide reliability measures that solve this problem. We then apply our methodology to a dataset on…

美国实际产出状态切换时间序列模型的有效性评估AI 解读

Two types of state-switching models for U.S. real output have been proposed: models that switch randomly between states and models that switch states deterministically, as in the threshold autoregressive model of Potter. These models have been justified primarily on how well they fit the sample data, yielding statistically significant estimates of the model coefficients. Here we propose a new approach to the evaluation of an estimated nonlinear time series model that…

修剪数据下的分布支配AI 解读

Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be influenced by data contamination. We examine a nonparametric approach to refining Lorenz-type comparisons and apply the technique to two important examples from the Luxembourg Income Study database.

含极端异常值金融时间序列的二阶滤波分布近似AI 解读

Particle filters are regularly used to obtain the filter distributions associated with state–space financial time series. The most common use today is the auxiliary particle filter (APF) method in conjunction with a first-order Taylor expansion of the log-likelihood. We argue that for series such as stock returns, which exhibit fairly frequent and extreme outliers, filters based on this first-order approximation can easily break down. However, an APF based on the much more…

动态随机前沿模型中的推断AI 解读

Abstract An important issue in models of technical efficiency measurement concerns the temporal behaviour of inefficiency. Consideration of dynamic models is necessary but inference in such models is complicated. In this paper we propose a stochastic frontier model that allows for technical inefficiency effects and dynamic technical inefficiency, and use Bayesian inference procedures organized around data augmentation techniques to provide inferences. Also provided are…

利用 Box–Cox 异方差回归建模企业规模分布AI 解读

Abstract Using the Box–Cox regression model with heteroscedasticity (BCHR), we re‐examine the size distribution of the Portuguese manufacturing firms studied by Machado and Mata ( 2000 ) using the Box–Cox quantile regression (BCQR) method. We show that the BCHR model compares favourably against the BCQR method. In particular, the BCHR model can answer the key questions addressed by the BCQR method, with the advantage that the estimated quantile functions are monotonic.…

含连续协变量的捕获—再捕获数据潜在边际模型AI 解读

We introduce a new family of latent class models for the analysis of capture–recapture data where continuous covariates are available. The present approach exploits recent advances in marginal parameterizations to model simultaneously, and conditionally on individual covariates, the size of the latent classes, the marginal probabilities of being captured by each list given the latent, and possible higher-order marginal interactions among lists conditionally on the latent. An…

广义线性潜变量模型的有界影响稳健估计AI 解读

Latent variable models are used for analyzing multivariate data. Recently, generalized linear latent variable models for categorical, metric, and mixed-type responses estimated via maximum likelihood (ML) have been proposed. Model deviations, such as data contamination, are shown analytically, using the influence function and through a simulation study, to seriously affect ML estimation. This article proposes a robust estimator that is made consistent using the basic…

全条件分布近似正态时的联合后验大样本近似AI 解读

Modern Bayesian statistical methods, such as Gibbs and Metropolis–Hastings sampling, were developed to liberate statisticians from the necessity of making large-sample assumptions and to facilitate the numerical approximation of problems that had previously been analytically intractable. Counter to this trend, we develop a method for constructing asymptotic joint posterior approximations based on models with k blocks of parameters and where the corresponding properly…

高维协变量下的切片逆回归AI 解读

Sliced inverse regression is a promising method for the estimation of the central dimension-reduction subspace (CDR space) in semiparametric regression models. It is particularly useful in tackling cases with high-dimensional covariates. In this article we study the asymptotic behavior of the estimate of the CDR space with high-dimensional covariates, that is, when the dimension of the covariates goes to infinity as the sample size goes to infinity. Strong and weak…

完全非参数协方差分析模型中的协变量效应检验AI 解读

Traditional inference questions in the analysis of covariance mainly focus on comparing different factor levels by adjusting for the continuous covariates, which are believed to also exert a significant effect on the outcome variable. Testing hypotheses about the covariate effects, although of substantial interest in many applications, has received relatively limited study in the semiparametric/nonparametric setting. In the context of the fully nonparametric analysis of…

利用两个随机过程预测死因—年龄特定死亡人数AI 解读

Mortality forecasts are critical information for assessing the health of a population and are necessary for making informed decisions about how best to direct health-related resources and activities. Timeliness in making health statistics available is crucial to identify and address current health problems. Being motivated to meet these needs, we propose a method to forecast the number of cause-age specific deaths through a two random processes model. Unlike the previous…

含内生时变协变量的不完整泊松数据的条件推断方法AI 解读

We investigate the effect of protease inhibitors (PIs) on the rate of emergency room (ER) visits among HIV-infected women from a longitudinal cohort study. One strategy for accounting for serial correlation in longitudinal studies is to assume that observations are independent, conditional on unit-specific nuisance parameters. It is possible to estimate these models using unconditional maximum likelihood, where the nuisance parameters are assigned a parametric distribution…

非高斯贝叶斯地统计建模AI 解读

Sampling models for geostatistical data are usually based on Gaussian processes. However, real data often display non-Gaussian features, such as heavy tails. In this article we propose a more flexible class of sampling models. We start from the spatial linear model that has a spatial trend plus a stationary Gaussian error process. We extend the sampling model to non-Gaussianity by including a scale parameter at each location. We make sure that we obtain a valid stochastic…

空间相关生存数据的半参数正态变换模型AI 解读

There is an emerging interest in modeling spatially correlated survival data in biomedical and epidemiologic studies. In this article we propose a new class of semiparametric normal transformation models for right-censored spatially correlated survival data. This class of models assumes that survival outcomes marginally follow a Cox proportional hazard model with unspecified baseline hazard, and their joint distribution is obtained by transforming survival outcomes to normal…

弯折缆线回归的理论与应用AI 解读

We use the so-called “bent-cable” model to describe natural phenomena that exhibit a potentially sharp change in slope. The model comprises two linear segments, joined smoothly by a quadratic bend. The class of bent cables includes, as a limiting case, the popular piecewise-linear model (with a sharp kink), otherwise known as the broken stick. Associated with bent-cable regression is the estimation of the bend-width parameter, through which the abruptness of the underlying…

通过交互粒子系统实现贝叶斯最优设计AI 解读

We propose a new stochastic algorithm for Bayesian-optimal design in nonlinear and high-dimensional contexts. Following Peter Müller, we solve an optimization problem by exploring the expected utility surface through Markov chain Monte Carlo simulations. The optimal design is the mode of this surface considered a probability distribution. Our algorithm relies on a “particle” method to efficiently explore high-dimensional multimodal surfaces, with simulated annealing to…

模型选择后置信区间的大样本最小覆盖概率AI 解读

We give a large-sample analysis of the minimal coverage probability of the usual confidence intervals for regression parameters when the underlying model is chosen by a “conservative” (or “overconsistent”) model selection procedure. We derive an upper bound for the large-sample limit minimal coverage probability of such intervals that applies to a large class of model selection procedures including the Akaike information criterion as well as various pretesting procedures.…

利用投影寻踪检测多元时间序列异常值AI 解读

In this article we use projection pursuit methods to develop a procedure for detecting outliers in a multivariate time series. We show that testing for outliers in some projection directions can be more powerful than testing the multivariate series directly. The optimal directions for detecting outliers are found by numerical optimization of the kurtosis coefficient of the projected series. We propose an iterative procedure to detect and handle multiple outliers based on a…

含治愈比例的生存数据半参数变换模型AI 解读

We propose a class of transformation models for survival data with a cure fraction. The class of transformation models is motivated by biological considerations and includes both the proportional hazards and the proportional odds cure models as two special cases. An efficient recursive algorithm is proposed to calculate the maximum likelihood estimators (MLEs). Furthermore, the MLEs for the regression coefficients are shown to be consistent and asymptotically normal, and…

二元数据模型检验中的自助法近似AI 解读

Consider a binary regression model in which the conditional expectation of a binary variable given an explanatory variable belongs to a parametric family. To check whether a sequence of independent and identically distributed observations belongs to such a parametric family, we use Kolmogorov–Smirnov and Cramér–von Mises type tests based on a marked empirical process introduced by Stute. We propose and study a new resampling scheme for a bootstrap in this setup to…

k 样本模型中与最佳者的 δ 等效性AI 解读

In recent work we introduced a general, a weak, and a strong partitioning principles for the construction of multiple decision procedures as multiple testing or selection procedures. Partitioning principles can be viewed as natural extensions of the closure principle and sometimes yield more powerful decision procedures. In this article we consider the problem of establishing equivalence with the best with respect to k treatment means, where equivalence is defined in terms…

交替治疗安排研究中的失效时间数据分析AI 解读

We develop statistical methods for designing and analyzing studies in which treatments are deliberately interrupted and reinitiated, but where interest lies in making inferences about continuous treatment use. We refer to such designs as alternating designs, because subjects alternate between periods in which they are taking the treatment of interest and periods when they are not. Our goals are to determine how to estimate the distribution of time to an event if the…

二元纵向数据半参数动态模型的推断AI 解读

This article deals with the analysis of a hierarchical semiparametric model for dynamic binary longitudinal responses. The main complicating components of the model are an unknown covariate function and serial correlation in the errors. Existing estimation methods for models with these features are of O(N3), where N is the total number of observations in the sample. Therefore, nonparametric estimation is largely infeasible when the sample size is large, as in typical in the…