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半强 GARCH 模型的拟最大似然估计AI 解读

This note proves the consistency and asymptotic normality of the quasi–maximum likelihood estimator (QMLE) of the parameters of a generalized autoregressive conditional heteroskedastic (GARCH) model with martingale difference centered squared innovations. The results are obtained under mild conditions and generalize and improve those in Lee and Hansen (1994, Econometric Theory 10, 29–52) for the local QMLE in semistrong GARCH(1,1) models. In particular, no restrictions on…

GARCH 模型参数设定误检验的一阶渐近理论AI 解读

This paper develops a framework for the construction and analysis of parametric misspecification tests for generalized autoregressive conditional heteroskedastic (GARCH) models, based on first-order asymptotic theory. The principal finding is that estimation effects from the correct specification of the conditional mean (regression) function can be asymptotically nonnegligible. This implies that certain procedures, such as the asymmetry tests of Engle and Ng (1993, Journal…

基于回归的季节性单位根检验AI 解读

The contribution of this paper is threefold. First, a characterization theorem of the subhypotheses comprising the seasonal unit root hypothesis is presented that provides a precise formulation of the alternative hypotheses associated with regression- based seasonal unit root tests. Second, it proposes regression-based tests for the seasonal unit root hypothesis that allow a general seasonal aspect for the data and are similar both exactly and asymptotically with respect to…

含中度整合与中度爆炸回归变量的协整系统极限理论AI 解读

An asymptotic theory is developed for multivariate regression in cointegrated systems whose variables are moderately integrated or moderately explosive in the sense that they have autoregressive roots of the form ρ ni = 1 + c i / n α , involving moderate deviations from unity when α ∈ (0, 1) and c i ∈ ℝ are constant parameters. When the data are moderately integrated in the stationary direction (with c i < 0), it is shown that least squares regression is consistent and…

区分随机游走与均值变化备择AI 解读

We study test procedures that detect structural breaks in underlying data sequences. In particular, we wish to discriminate between different reasons for these changes, such as (1) shifting means, (2) random walk behavior, and (3) constant means but innovations switching from stationary to difference stationary behavior. Almost all procedures presently available in the literature are simultaneously sensitive to all three types of alternatives. The test statistics under…

因子 GARCH 模型的渐近理论AI 解读

This paper investigates the asymptotic theory for a factor GARCH (generalized autoregressive conditional heteroskedasticity) model. Sufficient conditions for asymptotic stability and existence of moments are established. These conditions allow for volatility spillover and integrated GARCH. We then show the strong consistency and asymptotic normality of the quasi–maximum likelihood estimator (QMLE) of the model parameters. The results are obtained under the finiteness of the…

工具变量回归中多个参数的条件似然比检验AI 解读

For the problem of testing the hypothesis that all m coefficients of the right-hand-side endogenous variables in an instrumental variables (IV) regression are zero, the likelihood ratio (LR) test can, if the reduced form covariance matrix is known, be rendered similar by a conditioning argument. To exploit this fact requires knowledge of the relevant conditional cumulative distribution function (c.d.f.) of the LR statistic, but the statistic is a function of the smallest…

利用聚合数据贝叶斯估计随机系数选择模型AI 解读

Abstract This article discusses the use of Bayesian methods for estimating logit demand models using aggregate data. We analyze two different demand systems: independent samples and consumer panel. Under the first system, there is a different and independent random sample of N consumers in each period and each consumer makes only a single purchase decision. Under the second system, the same N consumers make a purchase decision in each of T periods. Interestingly, there…

带测量误差的部分线性模型变量选择AI 解读

This article focuses on variable selection for partially linear models when the covariates are measured with additive errors. We propose two classes of variable selection procedures, penalized least squares and penalized quantile regression, using the nonconvex penalized principle. The first procedure corrects the bias in the loss function caused by the measurement error by applying the so-called correction-for-attenuation approach, whereas the second procedure corrects the…

最近邻分类的贝叶斯重新评估AI 解读

The k-nearest-neighbor (knn) procedure is a well-known deterministic method used in supervised classification. This article proposes a reassessment of this approach as a statistical technique derived from a proper probabilistic model; in particular, we modify the assessment found in Holmes and Adams, and evaluated by Manocha and Girolami, where the underlying probabilistic model is not completely well defined. Once provided with a clear probabilistic basis for the knn…

簇相关误差线性模型的秩估计与相关推断AI 解读

R estimators based on the joint ranks (JR) of all the residuals have been developed over the last 20 years for fitting linear models with independently distributed errors. In this article, we extend these estimators to estimating the fixed effects in a linear model with cluster correlated continuous error distributions for general score functions. We discuss the asymptotic theory of the estimators and standard errors of the estimators. For the related mixed model with a…

利用随机小波表示一致分类非平稳时间序列AI 解读

Consider the situation when we have training data containing many time series having known group membership and testing data with unknown group membership. The goals are to find timescale features (using training data) that can best separate the groups, and to use these highly discriminant features to classify test data. We propose a method for classification using a bias-corrected nondecimated wavelet transform. Wavelets are ideal for identifying highly discriminant local…

基于最优预测的稳健响应变量变换AI 解读

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are…

基于似然的充分降维AI 解读

We obtain the maximum likelihood estimator of the central subspace under conditional normality of the predictors given the response. Analytically and in simulations we found that our new estimator can preform much better than sliced inverse regression, sliced average variance estimation and directional regression, and that it seems quite robust to deviations from normality.

具有半参数因子动态的时间序列建模AI 解读

High-dimensional regression problems, which reveal dynamic behavior, are typically analyzed by time propagation of a few number of factors. The inference on the whole system is then based on the low-dimensional time series analysis. Such high-dimensional problems occur frequently in many different fields of science. In this article we address the problem of inference when the factors and factor loadings are estimated by semiparametric methods. This more flexible modeling…

单倍型病例对照研究中兼顾稳健性与效率的收缩估计AI 解读

Case-control association studies often aim to investigate the role of genes and gene-environment interactions in terms of the underlying haplotypes (i.e., the combinations of alleles at multiple genetic loci along chromosomal regions). The goal of this article is to develop robust but efficient approaches to the estimation of disease odds-ratio parameters associated with haplotypes and haplotype-environment interactions. We consider "shrinkage" estimation techniques that can…

动态平滑系数模型的非参数分位数估计AI 解读

In this article, quantile regression methods are suggested for a class of smooth coefficient time series models. We use both local polynomial and local constant fitting schemes to estimate the smooth coefficients in a quantile framework. We establish the asymptotic properties of both the local polynomial and local constant estimators for α-mixing time series. Also, a bandwidth selector based on the nonparametric version of the Akaike information criterion is suggested,…

一般科学模型的确定及其资产定价应用AI 解读

We consider a consumption-based asset pricing model that uses habit persistence to overcome the known statistical inadequacies of the classical consumption-based asset pricing model. We find that the habit model fits reasonably well and agrees with results reported in the literature if conditional heteroskedasticity is suppressed but that it does not fit nor do results agree if conditional heteroskedasticity, well known to be present in financial market data, is allowed to…

气候模型集合中不确定性的贝叶斯建模AI 解读

Projections of future climate change caused by increasing greenhouse gases depend critically on numerical climate models coupling the ocean and atmosphere (global climate models [GCMs]). However, different models differ substantially in their projections, which raises the question of how the different models can best be combined into a probability distribution of future climate change. For this analysis, we have collected both current and future projected mean temperatures…

黑质神经元线粒体DNA缺失随机计算模型的贝叶斯仿真代理与校准AI 解读

This article considers the problem of parameter estimation for a stochastic biological model of mitochondrial DNA population dynamics using experimental data on deletion mutation accumulation. The stochastic model is an attempt to describe the hypothesized link between deletion accumulation and neuronal loss in the substantia nigra region of the human brain. Inference for the parameters of the model is complicated by the fact that the model is both analytically intractable…

事件依赖删失与终止下复发事件均值函数及治疗效应的稳健估计AI 解读

In clinical trials featuring recurrent clinical events, the definition and estimation of treatment effects involves a number of interesting issues, especially when loss to follow-up may be event-related and when terminal events such as death preclude the occurrence of further events. This paper discusses a clinical trial of breast cancer patients with bone metastases where the recurrent events are skeletal complications, and where patients may die during the trial. We argue…

GARCH 系数为零的检验：标准检验修正与相对效率比较AI 解读

This article is concerned with testing the nullity of coefficients in generalized autoregressive conditionally heteroscedastic (GARCH) models. The problem is nonstandard because the quasi-maximum likelihood estimator is subject to positivity constraints. This article establishes the asymptotic null and local alternative distributions of Wald, score, and quasi-likelihood ratio tests. Efficiency comparisons under fixed alternatives are considered. Two cases of special interest…

变量含测量误差问题中适应设计分布的局部多项式估计AI 解读

Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-variables context by exploiting its similarity with the deconvolution kernel density estimator. The generalization of the higher order versions of the estimator, however, is not straightforward and has remained an open problem for the last…

具有序列相关的多类别变量之间的依赖检验AI 解读

The contingency table literature on tests for dependence among discrete multicategory variables is extensive. Standard tests assume, however, that draws are independent and only limited results exist on the effect of serial dependency—a problem that is important in areas such as economics, finance, medical trials, and meteorology. This article proposes new tests of independence based on canonical correlations from dynamically augmented reduced rank regressions. The tests…