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双重惩罚下加性分位数回归模型的半参数估计AI 解读

In this article, we propose a model selection and semiparametric estimation method for additive models in the context of quantile regression problems. In particular, we are interested in finding nonzero components as well as linear components in the conditional quantile function. Our approach is based on spline approximation for the components aided by two Smoothly Clipped Absolute Deviation (SCAD) penalty terms. The advantage of our approach is that one can automatically…

区间抽样下二元生存数据分析及癌症流行病学应用AI 解读

In biomedical studies, ordered bivariate survival data are frequently encountered when bivariate failure events are used as outcomes to identify the progression of a disease. In cancer studies, interest could be focused on bivariate failure times, for example, time from birth to cancer onset and time from cancer onset to death. This paper considers a sampling scheme, termed interval sampling, in which the first failure event is identified within a calendar time interval, the…

偏倚抽样数据下不变密度比模型的似然方法AI 解读

The full likelihood approach in statistical analysis is regarded as the most efficient means for estimation and inference. For complex length-biased failure time data, computational algorithms and theoretical properties are not readily available, especially when a likelihood function involves infinite-dimensional parameters. Relying on the invariance property of length-biased failure time data under the semiparametric density ratio model, we present two likelihood approaches…

变系数 Cox 模型的有效估计AI 解读

A proportional hazards model with varying coefficients allows one to examine the extent to which covariates interact nonlinearly with an exposure variable. A global partial likelihood method, in contrast with the local partial likelihood method of Fan et al. (2006), is proposed for estimation of varying coefficient functions. The proposed estimators are proved to be consistent and asymptotically normal. Semiparametric efficiency of the estimators is demonstrated in terms of…

因果中介分析的半参数理论：效率界、多重稳健性与敏感性分析AI 解读

Whilst estimation of the marginal (total) causal effect of a point exposure on an outcome is arguably the most common objective of experimental and observational studies in the health and social sciences, in recent years, investigators have also become increasingly interested in mediation analysis. Specifically, upon evaluating the total effect of the exposure, investigators routinely wish to make inferences about the direct or indirect pathways of the effect of the exposure…

基于稳健秩相关的变量筛选AI 解读

Independence screening is a variable selection method that uses a ranking criterion to select significant variables, particularly for statistical models with nonpolynomial dimensionality or “large $p$, small $n$” paradigms when $p$ can be as large as an exponential of the sample size $n$. In this paper we propose a robust rank correlation screening (RRCS) method to deal with ultra-high dimensional data. The new procedure is based on the Kendall $\tau$ correlation coefficient…

密度线性泛函的 Bernstein–von Mises 定理AI 解读

In this paper, we study the asymptotic posterior distribution of linear functionals of the density by deriving general conditions to obtain a semi-parametric version of the Bernstein–von Mises theorem. The special case of the cumulative distributive function, evaluated at a specific point, is widely considered. In particular, we show that for infinite-dimensional exponential families, under quite general assumptions, the asymptotic posterior distribution of the functional…

部分线性模型中的工具变量回归AI 解读

We consider the semiparametric regression Xtβ + φ (Z) where β and φ(.) are unknown slope coefficient vector and function, and where the variables (X, Z) are endogeneous. We propose necessary and sufficient conditions for the identification of the parameters in the presence of instrumental variables. We also focus on the estimation of β. An incorrect parametrization of φ generally leads to an inconsistent estimator of β, whereas consistent nonparametric estimators for β have…

截断与删失回归模型的半参数稳健估计AI 解读

Many estimation methods of truncated and censored regression models such as the maximum likelihood and symmetrically censored least squares (SCLS) are sensitive to outliers and data contamination as we document. Therefore, we propose a semiparametric general trimmed estimator (GTE) of truncated and censored regression, which is highly robust but relatively imprecise. To improve its performance, we also propose data-adaptive and one-step trimmed estimators. We derive the…

具有广义固定效应的非可分面板模型的非参数识别AI 解读

This paper extends the familiar notion of fixed effects to nonlinear structures with infinite-dimensional unobservables, like preferences. The main result is that a generalized version of differencing identifies local average responses (LARs) in nonseparable structures. In contrast to existing results, this does not require either substantial restrictions on functional form or independence between the persistent unobservables and the explanatory variables of interest, and it…

混合比例可变的回归混合模型：半参数方法AI 解读

In this article, we study a class of semiparametric mixtures of regression models, in which the regression functions are linear functions of the predictors, but the mixing proportions are smoothing functions of a covariate. We propose a one-step backfitting estimation procedure to achieve the optimal convergence rates for both regression parameters and the nonparametric functions of mixing proportions. We derive the asymptotic bias and variance of the one-step estimate, and…

初始抗逆转录病毒方案失败后早期与延迟换药的效果评估AI 解读

The current goal of initial antiretroviral (ARV) therapy is suppression of plasma human immunodeficiency virus (HIV)-1 RNA levels to below 200 copies per milliliter. A proportion of HIV-infected patients who initiate antiretroviral therapy in clinical practice or antiretroviral clinical trials either fail to suppress HIV-1 RNA or have HIV-1 RNA levels rebound on therapy. Frequently, these patients have sustained CD4 cell counts responses and limited or no clinical symptoms…

面板数据中时间趋势异质性的新估计方法AI 解读

This paper introduces a new estimation method for arbitrary temporal heterogeneity in panel data models. The paper provides a semiparametric method for estimating general patterns of cross-sectional specific time trends. The methods proposed in the paper are related to principal component analysis and estimate the time-varying trend effects using a small number of common functions calculated from the data. An important application for the new estimator is in the estimation…

不完全信息博弈的成对差分估计AI 解读

This paper contributes to the literature on econometric estimation of incomplete information games with Nash equilibrium behavior by introducing a two-step estimation procedure that makes no parametric assumptions about the distribution of unobservable payoffs shocks. Instead, its asymptotic properties rely on assuming only that these distributions satisfy an invertibility condition, and that the underlying equilibrium selection mechanism is degenerate. Our methodology…

采购拍卖中的风险厌恶与非对称性：识别、估计及建筑采购应用AI 解读

This article studies a model of asymmetric risk averse bidding within the independent private value paradigm. The inherent asymmetry in cost and risk aversion imposes an original restriction on the observed bid data, an exact equality which leads to the model semiparametric identification and estimation. The unobserved arguments of this equality need to be simulated in order to estimate the bidders’ Constant Relative Risk Aversion or Constant Absolute Risk Aversion…

具有信号关联性的第一价格密封投标拍卖模型的半参数估计AI 解读

Within the affiliated private-values paradigm, we develop a tractable empirical model of equilibrium behaviour at first-price, sealed-bid auctions. The model is non-parametrically identified, but the rate of convergence in estimation is slow when the number of bidders is even moderately large, so we develop a semiparametric estimation strategy, focusing on the Archimedean family of copulae and implementing this framework using particular members—the Clayton, Frank, and…

经验拍卖模型的有效局部工具变量估计AI 解读

In this paper we examine semiparametric efficiency bounds and efficient estimators for the case of a linear local instrument variable (LIV) model under the assumptions studied in Abadie et al. (2002). We apply the semiparametrically efficient estimation method to analyze the relation between bid dispersion and early bidding in an online auction dataset, which is collected from a natural experiment conducted in Nekipelov (2007). The results confirm the theoretical findings…

半参数回归模型估计中的 Robbins–Monro 程序AI 解读

This paper is devoted to the parametric estimation of a shift together with the nonparametric estimation of a regression function in a semiparametric regression model. We implement a very efficient and easy to handle Robbins–Monro procedure. On the one hand, we propose a stochastic algorithm similar to that of Robbins–Monro in order to estimate the shift parameter. A preliminary evaluation of the regression function is not necessary to estimate the shift parameter. On the…

截断回归模型的半参数估计AI 解读

This paper proposes a new semiparametric estimator for the truncated regression model under the independence restriction. Many existing approaches such as those in Lee (1992) and Honoré and Powell (1994) are moment-based methods, whereas our approach makes use of the entire truncated distribution. As a result, our approach is expected to require weaker identification and to have more favorable performance. Our simulation results suggest that our estimator outperforms that of…

GARCH 均值模型中的半参数推断AI 解读

A new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and GARCH-type underlying volatility is introduced. Based on the profile likelihood approach, it does not rely on any initial parametric estimator of the conditional mean function, and it is under stated conditions consistent, asymptotically normal, and efficient, i.e., it achieves the semiparametric lower bound. A sampling experiment provides finite sample…

空间依赖回归的统计推断AI 解读

Central limit theorems are developed for instrumental variables estimates of linear and semiparametric partly linear regression models for spatial data. General forms of spatial dependence and heterogeneity in explanatory variables and unobservable disturbances are permitted. We discuss estimation of the variance matrix, including estimates that are robust to disturbance heteroscedasticity and/or dependence. A Monte Carlo study of finite-sample performance is included. In an…

部分变系数动态模型的半参数分位数回归估计AI 解读

We study quantile regression estimation for dynamic models with partially varying coefficients so that the values of some coefficients may be functions of informative covariates. Estimation of both parametric and nonparametric functional coefficients are proposed. In particular, we propose a three stage semiparametric procedure. Both consistency and asymptotic normality of the proposed estimators are derived. We demonstrate that the parametric estimators are root-n…

通过边际积分估计半参数面板数据模型AI 解读

We propose an alternative method for estimating the nonlinear component in semiparametric panel data models. Our method is based on marginal integration that allows us to recover the nonlinear component from an additive regression structure that results from the first differencing transformation. We characterize the asymptotic behavior of our estimator. We also extend the methodology to treat panel data models with two-way effects. Monte Carlo simulations show that our…

空间自回归模型的半参数 GMM 估计AI 解读

We propose semiparametric GMM estimation of semiparametric spatial autoregressive (SAR) models under weak moment conditions. In comparison with the quasi-maximum-likelihood-based semiparametric estimator of Su and Jin (2010), we allow for both heteroscedasticity and spatial dependence in the error terms. We derive the limiting distributions of our estimators for both the parametric and nonparametric components in the model and demonstrate the estimator of the parametric…