跳到正文
收录说明
收录范围
保留计量方法研究、相关统计基础,以及实质涉及计量方法的应用、教程、比较和综述。书评、刊务及明确无关内容不公开;身份或相关性证据不足的记录保留待核,补充可靠材料后可重新判断。
当前期刊来源见下方官网链接及期刊目录。综合经济学与金融期刊逐篇筛查计量方向,证据不足时暂不公开。正刊、在线优先论文和已核实接收稿合并展示;按标题、可靠摘要、目录及身份匹配的出版社 JEL 分类核验相关性;计量类 JEL 与摘要相互印证,无 JEL 不直接排除。历史回补以可取得的注册题录和目录为准,不等于覆盖全部纸本。
日期与排序
默认按最近发表排序:正刊使用刊期,待刊使用上线日期;缺少上线日期时,排序参考登记或首次收录时间,并在卡片注明。更多筛选可选择出版状态和日期口径;卷期依据出版社元数据,不因待刊时间较长而推定已编入正刊。仅有月份或年份时,日期区间相交也会纳入。

日期精度:到日 1308 篇 · 到月 1915 篇 · 到年 331 篇 · 未提供 1 篇

分类与引用
领域和方法依据题名、摘要初步分类,可人工修正;分类不代表论文质量。引用数采用 OpenAlex 单条关联记录,不合计版本。
极大与准极大似然:极大似然、准极大似然与复合似然。
更新与 AI 解读
正常题录、可靠摘要与引用同步继续;日、周、月简报按核实的发表与修订日期汇总,历史补录保留在文献库。AI 解读依据可靠摘要或已核实原文片段,已有解读保留供阅读参考;缺少可靠材料的条目保持待解读,浏览页面不会触发生成。
3,555 篇论文
导出
BibTeX ↓RIS ↓RSS 订阅 ↗

Application of ‘Delete = Replace’ to Deletion Diagnostics for Variance Component Estimation in the Linear Mixed Model

“删除等于替换”在线性混合模型方差分量删除诊断中的应用

Summary ‘Delete = replace’ is a powerful and intuitive modelling identity. This paper extends previous work by stating and proving the identity in more general terms and extending its application to deletion diagnostics for estimates of variance components obtained by restricted maximum likelihood estimation for the linear mixed model. We present a new, fast, transparent and approximate computational procedure, arising as a by-product of the fitting process. We illustrate…

AI 解读阅读原文 ↗BibTeX ↓

MM algorithms for generalized Bradley-Terry models

广义 Bradley–Terry 模型的 MM 算法

The Bradley-Terry model for paired comparisons is a simple and much-studied means to describe the probabilities of the possible outcomes when individuals are judged against one another in pairs. Among the many studies of the model in the past 75 years, numerous authors have generalized it in several directions, sometimes providing iterative algorithms for obtaining maximum likelihood estimates for the generalizations. Building on a theory of algorithms known by the initials…

AI 解读阅读原文 ↗BibTeX ↓

Multinomial-Poisson homogeneous models for contingency tables

列联表的多项分布—泊松齐次模型

A unified approach to maximum likelihood inference for a broad, new class of contingency table models is presented. The model class comprises multinomial-Poisson homogeneous (MPH) models, which can be characterized by an independent sampling plan and a system of homogeneous constraints, h(m) = 0, where m is the vector of expected table counts. Maximum likelihood (ML) fitting and large-sample inference for MPH models are described. The MPH models are partitioned into…

AI 解读阅读原文 ↗BibTeX ↓

Consistent estimation of distributions with type II bias with applications in competing risks problems

具有第二类偏向的分布的一致估计及竞争风险应用

A random variable X is symmetric about 0 if X and -X have the same distribution. There is a large literature on the estimation of a distribution function (DF) under the symmetry restriction and tests for checking this symmetry assumption. Often the alternative describes some notion of skewness or one-sided bias. Various notions can be described by an ordering of the distributions of X and -X. One such important ordering is that $P(0<X<X\le x)-P(-x\le X<0)$ is increasing in $x<0$…

AI 解读阅读原文 ↗BibTeX ↓

Estimation of proportional covariances in the presene of certain linear restrictions

Proportionality of covariance matrices of n independent p-dimensional normal distributions with the same type of linear restrictions of the inverse covariances is considered. Conditions for existence and uniqueness of the maximum likelihood estimator are obtained through the development of general results for scale-invariant natural exponential families.

阅读原文 ↗BibTeX ↓

EFFICIENT LIKELIHOOD INFERENCE IN NONSTATIONARY UNIVARIATE MODELS

非平稳单变量模型中的有效似然推断

Recent literature shows that embedding fractionally integrated time series models with spectral poles at the long-run and/or seasonal frequencies in autoregressive frameworks leads to estimators and test statistics with nonstandard limiting distributions. However, we demonstrate that when embedding such models in a general I(d) framework the resulting estimators and tests regain desirable properties from standard statistical analysis. We show the existence of a local time…

AI 解读阅读原文 ↗BibTeX ↓

Random Effects Estimators with many Instrumental Variables

多工具变量下的随机效应估计量

In this paper we propose a new estimator for a model with one endogenous regressor and many instrumental variables. Our motivation comes from the recent literature on the poor properties of standard instrumental variables estimators when the instrumental variables are weakly correlated with the endogenous regressor. Our proposed estimator puts a random coefficients structure on the relation between the endogenous regressor and the instruments. The variance of the random…

AI 解读阅读原文 ↗BibTeX ↓

Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators

GMM 与广义经验似然估计量的高阶性质

In an effort to improve the small sample properties of generalized method of mo-ments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilt-ing estimators. We show that these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) estimators. We use this structure to compare their higher order asymptotic properties. We find…

AI 解读阅读原文 ↗BibTeX ↓

Observation-driven models for Poisson counts

Poisson计数的观测驱动模型

This paper is concerned with a general class of observation‐driven models for time series of counts whose conditional distributions given past observations and explanatory variables follow a Poisson distribution. These models provide a flexible framework for modelling a wide range of dependence structures. Conditions for stationarity and ergodicity of these processes are established from which the large‐sample properties of the maximum likelihood estimators can be derived.…

AI 解读阅读原文 ↗BibTeX ↓

Kernel-type estimators for the extreme value index

极值指数的核型估计量

A large part of the theory of extreme value index estimation is developed for positive extreme value indices. The best-known estimator of a positive extreme value index is probably the Hill estimator. This estimator belongs to the category of moment estimators, but can also be interpreted as a quasi-maximum likelihood estimator. It has been generalized to a kernel-type estimator, but this kernel-type estimator can, similarly to the Hill estimator, only be used for the…

AI 解读阅读原文 ↗BibTeX ↓

Bayesian bootstrap for proportional hazards models

比例风险模型的贝叶斯自助法

We propose two Bayesian bootstrap extensions, the binomial and Poisson forms, for proportional hazards models. The binomial form Bayesian bootstrap is the limit of the posterior distribution with a beta process prior as the amount of the prior information vanishes, and thus can be considered as a default nonparametric Bayesian analysis. It is also the same as Lo's Bayesian bootstrap for censored data when covariates are absent. The Poisson form Bayesian bootstrap is…

AI 解读阅读原文 ↗BibTeX ↓

A full-factor multivariate GARCH model

全因子多元 GARCH 模型

A new multivariate time series model with time varying conditional variances and covariances is presented and analysed. A complete analysis of the proposed model is presented consisting of parameter estimation, model selection and volatility prediction. Classical and Bayesian techniques are used for the estimation of the model parameters. It turns out that the construction of our proposed model allows easy maximum likelihood estimation and construction of well-mixing Markov…

AI 解读阅读原文 ↗BibTeX ↓

Free-Knot Polynomial Splines with Confidence Intervals

自由结点多项式样条及其置信区间

Summary We construct approximate confidence intervals for a nonparametric regression function, using polynomial splines with free-knot locations. The number of knots is determined by generalized cross-validation. The estimates of knot locations and coefficients are obtained through a non-linear least squares solution that corresponds to the maximum likelihood estimate. Confidence intervals are then constructed based on the asymptotic distribution of the maximum likelihood…

AI 解读阅读原文 ↗BibTeX ↓

Accommodating Stochastic Departures from Percentile Invariance in Causal Models

因果模型中对百分位不变性随机偏离的处理

Summary Consider a clinical trial in which participants are randomized to a single-dose treatment or a placebo control and assume that the adherence level is accurately recorded. If the treatment is effective, then good adherers in the treatment group should do better than poor adherers because they received more drug; the treatment group data follow a dose–response curve. But, good adherers to the placebo often do better than poor adherers, so the observed…

AI 解读阅读原文 ↗BibTeX ↓

Cointegration in Fractional Systems with Unknown Integration Orders

积分阶数未知的分数系统中的协整

Cointegrated bivariate nonstationary time series are considered in a fractional context, without allowance for deterministic trends. Both the observable series and the cointegrating error can be fractional processes. The familiar situation in which the respective integration orders are 1 and 0 is nested, but these values have typically been assumed known. We allow one or more of them to be unknown real values, in which case Robinson and Marinucci (2001, 2003) have justified…

AI 解读阅读原文 ↗BibTeX ↓

End-of-Sample Instability Tests

样本末端不稳定性检验

This paper considers tests for structural instability of short duration, such as at the end of the sample. The key feature of the testing problem is that the number, m, of observations in the period of potential change is relatively small—possibly as small as one. The well-known F test of Chow (1960) for this problem only applies in a linear regression model with normally distributed iid errors and strictly exogenous regressors, even when the total number of observations,…

AI 解读阅读原文 ↗BibTeX ↓

The Estimation of Dynamic Bivariate Mixture Models

动态二元混合模型的估计

Watanabe estimated the dynamic bivariate mixture models introduced by Tauchen and Pitts and modified by Andersen using a Bayesian method via Markov chain Monte Carlo techniques. Based on a maximum likelihood method via efficient importance sampling, Liesenfeld and Richard obtained estimates that are significantly different from those of Watanabe. This note corrects the error in the multimove sampler used by Watanabe and reproduces all analyses in the work of Watanabe using a…

AI 解读阅读原文 ↗BibTeX ↓

Estimation of Dynamic Bivariate Mixture Models

动态二元混合模型的估计

This note compares a Bayesian Markov chain Monte Carlo approach implemented by Watanabe with a maximum likelihood ML approach based on an efficient importance sampling procedure to estimate dynamic bivariate mixture models. In these models, stock price volatility and trading volume are jointly directed by the unobservable number of price-relevant information arrivals, which is specified as a serially correlated random variable. It is shown that the efficient importance…

AI 解读阅读原文 ↗BibTeX ↓

Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroscedastic Dynamic Regression Models With Student t Innovations

含多元 t 创新的条件异方差动态回归模型:极大似然估计与推断

Hessian, and information matrix of conditionally heteroscedastic dynamic regression models when the conditional distribution is multivariate t. We also derive one-sided and two-sided Lagrange multiplier tests for multivariate normality versus multivariate t based on the first two moments of the squared norm of the standardized innovations evaluated at the Gaussian pseudo-maximum likelihood estimators of the conditional mean and variance parameters. Finally, we illustrate our…

AI 解读阅读原文 ↗BibTeX ↓

Characterizing Additively Closed Discrete Models by a Property of Their Maximum Likelihood Estimators, With an Application to Generalized Hermite Distributions

由极大似然估计性质刻画加法封闭离散模型及其广义 Hermite 应用

This article reports on two-parameter count distributions (satisfying very general conditions) that are closed under addition so that their maximum likelihood estimator (MLE) of the population mean is the sample mean. The most important of these in practice, the generalized Hermite distribution, is analyzed, and a necessary and sufficient condition is given to ensure that the MLE is the solution of likelihood equations. Score test to contrast the Poisson assumption is…

AI 解读阅读原文 ↗BibTeX ↓

Optimality, Variability, Power

最优性、变异性与检验功效

We provide a theoretical template for the comparison of response-adaptive randomization procedures for clinical trials. Using a Taylor expansion of the noncentrality parameter of the usual chi-squared test for binary responses, we show explicitly the relationship among the target allocation proportion, the bias of the randomization procedure from that target, and the variability induced by the randomization procedure. We also generalize this relationship for more than two…

AI 解读阅读原文 ↗BibTeX ↓

How Much Does the Far Future Matter? A Hierarchical Bayesian Analysis of the Public's Willingness to Mitigate Ecological Impacts of Climate Change

遥远未来有多重要?公众减缓气候生态影响意愿的层级贝叶斯分析

How much does the far future matter? This question lies at the heart of many important environmental policy issues, such as global climate change, biodiversity loss, and the disposal of radioactive waste. Although philosophers, experts, and others offer their viewpoints on this deep question, the solution to many environmental problems lies in the willingness of the public to bear significant costs now to make the far future a better place. Short of national plebiscites, the…

AI 解读阅读原文 ↗BibTeX ↓

Transform Estimation of Parameters for Stage-Frequency Data

阶段频数数据的参数变换估计

We consider multistage development models that occur in the maturation of biological organisms, disease progressions, and industrial processes. The situations that we address are distinguished by the essentially destructive sampling required to assess the stage reached by each individual. We develop robust estimators of stage-dependent maturation rates and overall death rates using method of moments based on Laplace transforms, for which we develop variance estimates under…

AI 解读阅读原文 ↗BibTeX ↓

Asymptotic Efficiency in Parametric Structural Models with Parameter-Dependent Support

支持集依赖参数的参数化结构模型中的渐近效率

In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting distributions of particular estimators in these models. In contrast, we study the problem of constructing efficient point estimators. We show that the maximum likelihood estimator is…

AI 解读阅读原文 ↗BibTeX ↓