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非平稳面板离散选择建模及其汇率制度选择应用AI 解读

This paper develops a regression limit theory for discrete choice nonstationary panels with large cross section (N) and time series (T) dimensions. Some results emerging from this theory are directly applicable in the wider context of M-estimation. This includes an extension of work by Wooldridge [Wooldridge, J.M., 1994. Estimation and Inference for Dependent Processes. In: Engle, R.F., McFadden, D.L. (Eds.). Handbook of Econometrics, vol. 4, North-Holland, Amsterdam] on the…

共同随机趋势的提取：理论与应用AI 解读

This paper investigates the statistical properties of estimators of the parameters and unobserved series for state space models with integrated time series. In particular, we derive the full asymptotic results for maximum likelihood estimation using the Kalman filter for a prototypical class of such models--those with a single latent common stochastic trend. Indeed, we establish the consistency and asymptotic mixed normality of the maximum likelihood estimator and show that…

基于两阶段已实现波动率的离散观测扩散过程估计AI 解读

This paper motivates and introduces a two-stage method of estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as developed in [Jacod, J., 1994. Limit of random measures associated with the increments of a Brownian semiartingal. Working paper, Laboratoire de Probabilities, Universite Pierre et Marie Curie, Paris] and [Barndorff-Nielsen, O., Shephard, N., 2002.…

分位数协整回归AI 解读

Quantile regression has important applications in risk management, portfolio optimization, and asset pricing. The current paper studies estimation, inference and financial applications of quantile regression with cointegrated time series. In addition, a new cointegration model with quantile-varying coefficients is proposed. In the proposed model, the value of cointegrating coefficients may be affected by the shocks and thus may vary over the innovation quantile. The proposed…

美国短期利率预测：灵活的预测组合方法AI 解读

This paper develops a flexible approach to combine forecasts of future spot rates with forecasts from time-series models or macroeconomic variables. We find empirical evidence that, accounting for both regimes in interest rate dynamics, and combining forecasts from different models, helps improve the out-of-sample forecasting performance for US short-term rates. Imposing restrictions from the expectations hypothesis on the forecasting model are found to help at long…

使用条件自回归期望分位数模型评估风险价值AI 解读

In this paper we propose a downside risk measure, the expectile-based Value at Risk (EVaR), which is more sensitive to the magnitude of extreme losses than the conventional quantile-based VaR (QVaR). The index [theta] of an EVaR is the relative cost of the expected margin shortfall and hence reflects the level of prudentiality. It is also shown that a given expectile corresponds to the quantiles with distinct tail probabilities under different distributions. Thus, an EVaR…

存在并列与近似并列时总体排名的置信区间AI 解读

Frequentist confidence intervals for population ranks and their statistical justifications are not well established, even though there is a great need for such procedures in practice. How do we assign confidence bounds for the ranks of health care facilities, schools, and financial institutions based on data that do not clearly separate the performance of different entities apart? The commonly used bootstrap-based frequentist confidence intervals and Bayesian intervals for…

以错误发现率控制探索显著性AI 解读

When testing a single hypothesis, it is common knowledge that increasing the sample size after nonsignificant results and repeating the hypothesis test several times at unadjusted critical levels inflates the overall Type I error rate severely. In contrast, if a large number of hypotheses are tested controlling the False Discovery Rate, such “hunting for significance” has asymptotically no impact on the error rate. More specifically, if the sample size is increased for all…

微阵列实验的序贯设计AI 解读

This article features online supplementary material.A critical aspect in the design of microarray studies is the determination of the sample size necessary to declare genes differentially expressed across different experimental conditions. In this article, we propose a sequential approach where the decision to stop the experiment depends on the accumulated microarray data. The study could stop whenever sufficient data have been accumulated to identify gene expression changes…

存在干扰参数时基于伪似然的先验分布AI 解读

Consider a model parameterized by θ == (ψ, λ), where ψ is the parameter of interest. The problem of eliminating the nuisance parameter λ can be tackled by resorting to a pseudo-likelihood function L**(ψ) for ψ—namely, a function of ψ only and the data y with properties similar to those of a likelihood function. If one treats L**(ψ) as a true likelihood, the posterior distribution π**(ψ | y) ∝ π(ψ)L**(ψ) for ψ can be considered, where π(ψ) is a prior distribution on ψ. The…

右删失生存数据的一类变换平均剩余寿命模型AI 解读

The mean residual life function is an attractive alternative to the survival function or the hazard function of a survival time in practice. It provides the remaining life expectancy of a subject surviving up to time t. In this study, we propose a class of transformed mean residual life models for fitting survival data under right censoring. To estimate the model parameters, we make use of the inverse probability of censoring weighting approach and develop a system of…

利用参数与半参数贝叶斯折点回归分析 SEER 癌症发生率AI 解读

Cancer is the second leading cause of death in the United States. Cancer incidence and mortality rates measure the progress against cancer; these rates are obtained from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute (NCI). Lung cancer has the highest mortality rate among all cancers, whereas prostate cancer has the highest number of new cases among males. In this article, we analyze the incidence rates of these two cancers,…

从生物关联微阵列实验推断基因功能关系的统计框架AI 解读

A major task in understanding biological processes is to elucidate the relationships between genes involved in the underlying biological pathways. Microarray data from an increasing number of biologically interrelated experiments now allows for more complete portrayals of functional gene relationships in the pathways. In current studies of gene relationships, the presence of expression dependencies attributable to the biologically interrelated experiments, however, has been…

识别警察拦截中种族偏差的双重稳健内部基准与错误发现率AI 解读

Allegations of racially biased policing are a contentious issue in many communities. Processes that flag potential problem officers have become a key component of risk management systems at major police departments. We present a statistical method to flag potential problem officers by blending three methodologies that are the focus of active research efforts: propensity score weighting, doubly robust estimation, and false discovery rates. Compared with other systems…

内禀自回归时空模型及其在汇总出生结局中的应用AI 解读

A class of hierarchical Bayesian models is proposed for adverse birth outcomes such as preterm birth, which are assumed to follow a conditional binomial distribution. The log-odds of an adverse outcome in a particular county, logit(pi), follow a linear model that includes observed covariates and normally-distributed random effects. Spatial dependence between neighboring regions is allowed for by including an intrinsically autoregressive (IAR) prior or an IAR convolution…

古代森林制图：利用化石花粉记录推断森林组成的时空趋势AI 解读

Ecologists use the relative abundance of fossil pollen in sediments to estimate how tree species abundances change over space and time. To predict historical forest composition and quantify the available information, we build a Bayesian hierarchical model of forest composition in central New England, USA, based on pollen in a network of ponds. The critical relationships between abundances of taxa in the pollen record and abundances as actual vegetation are estimated for the…

利用二元 von Mises 分布与贝叶斯非参数方法估计蛋白质构象角密度AI 解读

Interest in predicting protein backbone conformational angles has prompted the development of modeling and inference procedures for bivariate angular distributions. We present a Bayesian approach to density estimation for bivariate angular data that uses a Dirichlet process mixture model and a bivariate von Mises distribution. We derive the necessary full conditional distributions to fit the model, as well as the details for sampling from the posterior predictive…

动态 PET 数据的非参数残留函数分析：健康受试者脑部 FDG 研究AI 解读

Kinetic analysis is used to extract metabolic information from dynamic positron emission tomography (PET) uptake data. The theory of indicator dilutions, developed in the seminal work of Meier and Zierler (1954), provides a probabilistic framework for representation of PET tracer uptake data in terms of a convolution between an arterial input function and a tissue residue. The residue is a scaled survival function associated with tracer residence in the tissue. Nonparametric…

不同尺度下带删失的重复测量：玉米微阵列分析的贝叶斯方法AI 解读

We analyze data collected in a somatic embryogenesis experiment carried out on Zea mays at Iowa State University. The main objective of the study was to identify the set of genes in maize that actively participate in embryo development. Embryo tissue was sampled and analyzed at various time periods and under different mediums and light conditions. As is the case in many microarray experiments, the operator scanned each slide multiple times to find the slide-specific…

新生儿重症监护观察研究中等效与差异检验的敏感性分析AI 解读

In randomized experiments, it is sometimes important to demonstrate that two treatments do not differ greatly in their effects, or to demonstrate that the treatments have very different effects on one outcome but similar effects on another outcome. These “demonstrations” may take the form of rejecting a null hypothesis of inequivalence in an equivalence test, or rejecting a null hypothesis of equal and inequivalent effects on two outcomes. The procedures often express a…

高维主成分分析的一致性与稀疏性AI 解读

Principal components analysis (PCA) is a classic method for the reduction of dimensionality of data in the form of n observations (or cases) of a vector with p variables. Contemporary datasets often have p comparable with or even much larger than n. Our main assertions, in such settings, are (a) that some initial reduction in dimensionality is desirable before applying any PCA-type search for principal modes, and (b) the initial reduction in dimensionality is best achieved…

函数型数据的深度概念AI 解读

The statistical analysis of functional data is a growing need in many research areas. In particular, a robust methodology is important to study curves, which are the output of many experiments in applied statistics. As a starting point for this robust analysis, we propose, analyze, and apply a new definition of depth for functional observations based on the graphic representation of the curves. Given a collection of functions, it establishes the “centrality” of an…

从实验数据推断最优同伴分配AI 解读

This article studies the problem of optimally dividing individuals into peer groups to maximize social gains from heterogeneous peer effects. The specific setting analyzed here concerns efficient ways of allocating roommates in college dormitories. Using confidential data on a sample of Dartmouth College freshmen who were randomly assigned to be roommates, the article derives efficient roommate pairing rules, based on demographic and academic background, which maximize…

含截距与趋势的稳定 AR(1) 模型中的 Bartlett 修正AI 解读

Bartlett corrections are derived for testing hypotheses about the autoregressive parameter ρ in the stable (a) AR(1) model, (b) AR(1) model with intercept, (c) AR(1) model with intercept and linear trend. The correction is found explicitly as a function of ρ . In the models with deterministic terms, the correction factor is asymmetric in ρ . Furthermore, the Bartlett correction is monotonically increasing in ρ and tends to infinity when ρ approaches the stability boundary of…