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Panel estimates of a two‐tiered earnings frontier

双层收入前沿模型的面板估计

This paper uses panel data to estimate a two-tiered instead of a one-tiered frontier model. The innovation is to develop a two-step maximum likelihood procedure yielding consistent estimates of inefficiency, while at the same time accounting for heterogeneity. The model is applied by estimating a 'two-tiered' earnings function to obtain indices of worker and firm incomplete labour market wage information using panel data from the Panel Study of Income Dynamics (1969-84). The…

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Quasi-likelihood models and optimal inference

拟似然模型与最优推断

Consider an ergodic Markov chain on the real line, with parametric models for the conditional mean and variance of the transition distribution. Such a setting is an instance of a quasi-likelihood model. The customary estimator for the parameter is the maximum quasi-likelihood estimator. It is not efficient, but as good as the best estimator that ignores the parametric model for the conditional variance. We construct two efficient estimators. One is a convex combination of…

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A robust adjustment of the profile likelihood

剖面似然的稳健调整

Under mild misspecifications of model assumptions, maximum likelihood estimates often remain consistent and asymptotically normal. Asymptotic normality will often hold for the signed root of the likelihood ratio statistic and the score statistic as well. However, standard estimates of asymptotic variance are usually inconsistent. This occurs when Bartlett's second identity fails. In the manner of McCullagh and Tibshirani, a variance correction may be used to adjust the…

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On the asymptotic properties of a flexible hazard estimator

灵活风险率估计量的渐近性质

Suppose one has a stochastic time-dependent covariate $Z(t)$, and is interested in estimating the hazard relationship $\lambda(t|\overline{Z}(t)) = \omega(Z(t))$, where $\overline{Z}(t)$ denotes the history of $Z(t)$ up to and including time t. In this paper, we consider a model of the form $\exp(s_n(Z(t)))$, where $s_n(Z(t))$ is a spline of finite but arbitrary order, and investigate the behavior of the maximum likelihood estimator of the hazard as the number of knots in…

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REML estimation: asymptotic behavior and related topics

REML 估计:渐近行为及相关问题

The restricted maximum likelihood (REML) estimates of dispersion parameters (variance components) in a general (non-normal) mixed model are defined as solutions of the REML equations. In this paper, we show the REML estimates are consistent if the model is asymptotically identifiable and infinitely informative under the (location) invariant class, and are asymptotically normal (A.N.) if in addition the model is asymptotically nondegenerate. The result does not require…

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Analysing inflation by the fractionally integrated ARFIMA-GARCH model

用分数单整 ARFIMA–GARCH 模型分析通货膨胀

This paper considers the application of long-memory processes to describing inflation for 10 countries. We implement a new procedure to obtain approximate maximum likelihood estimates of an ARFIMA-GARCH process; which is fractionally integrated I(d) with a superimposed stationary ARMA component in its conditional mean. Additionally, this long-memory process is allowed to have GARCH type conditional heteroscedasticity. On analysing monthly post-World War II CPI inflation for…

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Asymptotically efficient estimation of the index of regular variation

正则变动指数的渐近有效估计

We propose a conditional MLE of the index of regular variation when the functional form of a slowly varying function is assumed known in the tail, and we study its asymptotic properties. We prove asymptotic normality of $P_{\theta}^{k_n}$, a probability measure whose density is the product of the joint conditional density of the $k_n$ largest order statistics from $F_{\theta} (x)$ given $Z_{n-k}$, the $$(n-k)$th order statistic, and a density of $Z_{n-k}$ with parameter $\the…

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Estimating the Occurrence Rate for Prevalent Survival Data in Competing Risks Models

竞争风险模型中现患生存数据的发生率估计

The problem of interest is the estimation of occurrence probabilities based on prevalent data in competing risks models. In the literature, the development of nonparametric methods has relied heavily on the independent competing risks assumption. The primary purpose of this article is to establish a statistical framework without excluding the possibility of dependence among competing risks. This is done through the use of crude hazard functions. The crude hazard functions…

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Computation of Maximum Likelihood Estimates in Association Models

关联模型中最大似然估计的计算

In association models for cross-classified data, computation of maximum likelihood estimates (MLE's) is relatively difficult due to the nonlinear constraints on the parameters. Currently available procedures based on the scoring algorithm for constrained maximum likelihood are relatively unreliable, and other cyclic procedures are relatively slow and do not provide estimated asymptotic standard deviations as by-products of calculations. To facilitate computations, it is…

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Marginal Regression Analysis of a Multivariate Binary Response

多元二元响应的边际回归分析

We propose the use of the mean parameter for regression analysis of a multivariate binary response. We model the association using dependence ratios defined in terms of the mean parameter, the components of which are the joint success probabilities of all orders. This permits flexible modelling of higher-order associations, using maximum likelihood estimation. We reanalyse two data sets, one with variable cluster size and the other a longitudinal data set with constant…

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Analysing incomplete individual employment histories using indirect inference

利用间接推断分析不完整的个人就业经历

In this paper we apply the Indirect Inference method to estimate the parameters of a semi-Markov transition model when the data are subject to a complex form of censoring. There is no explicit expression for the likelihood function, and therefore Maximum Likelihood estimation is computationally burdensome. The econometric methodology of Indirect Inference is first tested on simulated data under various assumptions about the distribution of spell durations and transitions.…

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Maximum Likelihood Estimation of the Differencing Parameter for Invertible Short and Long Memory Autoregressive Integrated Moving Average Models

可逆短记忆与长记忆 ARIMA 模型差分参数的最大似然估计

SUMMARY In practical applications of Box-Jenkins autoregressive integrated moving average (ARIMA) models, the number of times that the observed time series must be differenced to achieve approximate stationarity is usually determined by careful, but mostly informal, analysis of the differenced series. For many time series, some differencing seems appropriate, but taking the first or the second difference may be too strong. As an alternative, Hosking, and Granger and Joyeux…

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Exponential Inequalities for Martingales, with Application to Maximum Likelihood Estimation for Counting Processes

鞅的指数不等式及其在计数过程最大似然估计中的应用

We obtain an exponential probability inequality for martingales and a uniform probability inequality for the process $\int g dN$, where $N$ is a counting process and where $g$ varies within a class of predictable functions $\mathscr{G}$. For the latter, we use techniques from empirical process theory. The uniform inequality is shown to hold under certain entropy conditions on $\mathscr{G}$. As an application, we consider rates of convergence for (nonparametric) maximum…

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Problems with the Asymptotic Theory of Maximum Likelihood Estimation in Integrated and Cointegrated Systems

单整与协整系统中极大似然估计渐近理论的困难

Problems with the asymptotic theory of nonlinear maximum likelihood estimation in integrated and cointegrated systems are discussed in this paper. One problem is that standard proofs of consistency generally do not apply; another one is that, even if the consistency has been established, it can be difficult to deduce the limiting distribution of a maximum likelihood estimator from a conventional Taylor series expansion of the score vector. It is argued in this paper that the…

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Multivariate Discriminant Analysis and Maximum Penalized Likelihood Density Estimation

多元判别分析与最大惩罚似然密度估计

SUMMARY A new theoretical point of view is discussed in the framework of density estimation. The multivariate true density, viewed as a prior or penalizing factor in a Bayesian framework, is modelled by a Gibbs potential. Estimating the density consists in maximizing the posterior. For efficiency of time, we are interested in an approximate estimator f̂ = Bπ of the true density f, where B is a stochastic operator and π is the raw histogram. Then, we investigate the…

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Regression Models for a Bivariate Discrete and Continuous Outcome with Clustering

具有聚类结构的离散与连续二元结局回归模型

Developmental toxicity studies of laboratory animals play a crucial role in the testing and regulation of chemicals and pharmaceutical compounds. Exposure to developmental toxicants typically causes a variety of adverse effects, such as fetal malformations and reduced fetal weight at term. In this article, we discuss regression methods for jointly analyzing bivariate discrete and continuous outcomes that are motivated by the statistical problems that arise in analyzing data…

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Estimators of Odds Ratio Regression Parameters in Matched Case-Control Studies with Covariate Measurement Error

协变量存在测量误差的匹配病例对照研究中优势比回归参数的估计

This article studies estimators of the odds ratio and odds ratio regression parameters in finely matched case-control studies containing a binary exposure of primary interest and subject-specific covariates that are subject to measurement error. A retrospective logistic regression model for the binary exposure variable is used. The effect of measurement errors on the conditional maximum likelihood estimator is determined. Three alternatives are considered: bias-corrected,…

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Inference for Likelihood Ratio Ordering in the Two-Sample Problem

两样本问题中似然比序的统计推断

We obtain the maximum likelihood estimators of two multinomial probability vectors under the constraint that they are likelihood ratio ordered. We extend this estimation approach to the case of two univariate distributions and show strong consistency of the estimators. We also derive and study the asymptotic distribution of the likelihood ratio statistic for testing the equality of two discrete probability distributions against the alternative that one distribution is…

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A Saturated Model for Analyzing Exchangeable Binary Data: Applications to Clinical and Developmental Toxicity Studies

分析可交换二元数据的饱和模型:临床与发育毒性研究应用

Correlated binary data occur very frequently in statistical practice. In many applications, it is reasonable to assume that data from the same cluster are exchangeable. Such data are commonly encountered in cluster sample surveys, teratological experiments, ophthalmologic and otolaryngologic studies, and other clinical trials. The standard methods of analyzing these data include the use of beta-binomial models and generalized estimating equations with third and fourth…

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Threshold Models for Combination Data from Reproductive and Developmental Experiments

生殖与发育实验中联合暴露数据的阈值模型

In risk assessment, thresholds are generally believed to exist for toxic reproductive and developmental agents. Therefore, dose combinations exist below the threshold where the response is not distinguishable from background and above the threshold where a dose-response trend results. Because data from combination experiments are more reflective of human exposure to environmental agents, threshold models that incorporate the effect of interactions among these agents are…

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Estimating Products in Forensic Identification Using DNA Profiles

基于 DNA 图谱的法医识别中的参数乘积估计

In many areas, such as reliability and forensic identification, it is of interest to estimate a product of unknown parameters, each of which is estimated from test data. The maximum likelihood estimator usually used in both applications is approximately unbiased but has an asymmetric sampling distribution, particularly when the sample size is not large. Consequently, most estimates understate the parameter value, often substantially, and this may be a serious drawback if…

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