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Fixed-domain asymptotics for a subclass of Matérn-type Gaussian random fields

一类 Matérn 型高斯随机场的固定域渐近理论

Stein [Statist. Sci. 4 (1989) 432–433] proposed the Matérn-type Gaussian random fields as a very flexible class of models for computer experiments. This article considers a subclass of these models that are exactly once mean square differentiable. In particular, the likelihood function is determined in closed form, and under mild conditions the sieve maximum likelihood estimators for the parameters of the covariance function are shown to be weakly consistent with respect to…

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Penalized log-likelihood estimation for partly linear transformation models with current status data

现时状态数据下部分线性变换模型的惩罚对数似然估计

We consider partly linear transformation models applied to current status data. The unknown quantities are the transformation function, a linear regression parameter and a nonparametric regression effect. It is shown that the penalized MLE for the regression parameter is asymptotically normal and efficient and converges at the parametric rate, although the penalized MLE for the transformation function and nonparametric regression effect are only n1/3 consistent. Inference…

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Asymptotic normality of the Lk-error of the Grenander estimator

Grenander 估计量的 Lk 误差渐近正态性

We investigate the limit behavior of the \(L_k\)-distance between a decreasing density \(f\) and its nonparametric maximum likelihood estimator \(\hat{f}_n\) for \(k \geq 1\). Due to the inconsistency of \(\hat{f}_n\) at zero, the case \(k = 2.5\) turns out to be a kind of transition point. We extend asymptotic normality of the \(L_1\)-distance to the \(L_k\)-distance for \(1 \leq k < 2.5\), and obtain the analogous limiting result for a modification of the \(L_k\)-distance…

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Asymptotic results for maximum likelihood estimators in joint analysis of repeated measurements and survival time

重复测量与生存时间联合分析中极大似然估计的渐近结果

Maximum likelihood estimation has been extensively used in the joint analysis of repeated measurements and survival time. However, there is a lack of theoretical justification of the asymptotic properties for the maximum likelihood estimators. This paper intends to fill this gap. Specifically, we prove the consistency of the maximum likelihood estimators and derive their asymptotic distributions. The maximum likelihood estimators are shown to be semiparametrically efficient.

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Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects

具有嵌套随机效应的受限与离散因变量模型的最大似然估计

Gauss-Hermite quadrature is often used to evaluate and maximize the likelihood for random component probit models. Unfortunately, the estimates are biased for large cluster sizes and/or intraclass correlations. We show that adaptive quadrature largely overcomes these problems. We then extend the adaptive quadrature approach to general random coefficient models with limited and discrete dependent variables. The models can include several nested random effects (intercepts and…

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ASYMPTOTICS OF THE QMLE FOR A CLASS OF ARCH(q) MODELS

一类 ARCH(q) 模型准极大似然估计的渐近性质

Strong consistency and asymptotic normality are established for the quasi-maximum likelihood estimator for a class of ARCH(q) models. The conditions are that the ARCH process is geometrically ergodic with a moment of arbitrarily small order. Furthermore for consistency, we assume that the second-order moment exists for the nondegenerate rescaled errors and, similarly, that the fourth-order moment exists for asymptotic normality to hold. Contrary to existing literature on…

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Minimum distance estimation for the logistic regression model

Logistic 回归模型的最小距离估计

It is well known that the maximum likelihood fit of the logistic regression parameters can be greatly affected by atypical observations. Several robust alternatives have been proposed. However, if we consider the model from the case-control viewpoint, it is clear that current techniques can exhibit poor behaviour in many common situations. A new robust class of estimation procedures is introduced. The estimators are constructed via a minimum distance approach after…

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Smooth quantile ratio estimation

平滑分位数比估计

We propose a novel approach to estimating the mean difference between two highly skewed distributions. The method, which we call smooth quantile ratio estimation, smooths, over percentiles, the ratio of the quantiles of the two distributions. The method defines a large class of estimators, including the sample mean difference, the maximum likelihood estimator under log-normal samples and the L-estimator. We derive asymptotic properties such as consistency and asymptotic…

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A semiparametric regression cure model with current status data

This paper considers the analysis of current status data with a cured proportion in the population using a mixture model that combines a logistic regression formulation for the probability of cure with a semiparametric regression model for the time to occurrence of the event. The semiparametric regression model belongs to the flexible class of partly linear models that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A…

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A note on composite likelihood inference and model selection

复合似然推断与模型选择札记

A composite likelihood consists of a combination of valid likelihood objects, usually related to small subsets of data. The merit of composite likelihood is to reduce the computational complexity so that it is possible to deal with large datasets and very complex models, even when the use of standard likelihood or Bayesian methods is not feasible. In this paper, we aim to suggest an integrated, general approach to inference and model selection using composite likelihood…

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On Nonparametric Maximum Likelihood Estimation with Interval Censoring and Left Truncation

区间删失与左截断下的非参数极大似然估计

Summary A graph theoretical approach is employed to describe the support set of the nonparametric maximum likelihood estimator for the cumulative distribution function given interval-censored and left-truncated data. A necessary and sufficient condition for the existence of a nonparametric maximum likelihood estimator is then derived. Two previously analysed data sets are revisited.

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Estimating the Proportion of True Null Hypotheses, with application to DNA Microarray Data

真实零假设比例的估计及其在 DNA 微阵列数据中的应用

Summary We consider the problem of estimating the proportion of true null hypotheses, π0, in a multiple-hypothesis set-up. The tests are based on observed p-values. We first review published estimators based on the estimator that was suggested by Schweder and Spjøtvoll. Then we derive new estimators based on nonparametric maximum likelihood estimation of the p-value density, restricting to decreasing and convex decreasing densities. The estimators of π0 are all derived under…

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Estimated Estimating Equations: Semiparametric Inference for Clustered and Longitudinal Data

估计型估计方程:聚类与纵向数据的半参数推断

Summary We introduce a flexible marginal modelling approach for statistical inference for clustered and longitudinal data under minimal assumptions. This estimated estimating equations approach is semiparametric and the proposed models are fitted by quasi-likelihood regression, where the unknown marginal means are a function of the fixed effects linear predictor with unknown smooth link, and variance–covariance is an unknown smooth function of the marginal means. We propose…

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Local Model Uncertainty and Incomplete-Data Bias (With Discussion)

局部模型不确定性与不完整数据偏差(含讨论)

Summary Problems of the analysis of data with incomplete observations are all too familiar in statistics. They are doubly difficult if we are also uncertain about the choice of model. We propose a general formulation for the discussion of such problems and develop approximations to the resulting bias of maximum likelihood estimates on the assumption that model departures are small. Loss of efficiency in parameter estimation due to incompleteness in the data has a dual…

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Frailty Survival Model Analysis of the National Deceased Donor Kidney Transplant Dataset Using Poisson Variance Structures

利用泊松方差结构分析亡故供者肾移植数据的脆弱性生存模型

In a recent study of transplant outcomes, donor age, cerebrovascular accident as the cause of death (CVA), renal insufficiency (serum creatinine >1.5 mg/dL), and history of hypertension have been identified as donor factors associated with elevated risk of kidney transplant failure. It is of great interest to know whether there remain other unmeasured donor factors associated with elevated risk of graft failure. In this article we study a sample of 6,024 deceased donor…

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Hierarchical Graphical Models

层级图模型

There is continued debate regarding the exact relation between lower cholesterol levels and increased respiratory disease mortality. One of the goals of this study is to reveal the relationship between subcomponents of cholesterol and pulmonary function. We consider the subcomponents of total cholesterol, namely high-density lipoprotein cholesterol and low-density lipoprotein cholesterol, to investigate the relationship of cholesterol levels with pulmonary function in a…

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Estimation in the Mixture of Markov Chains Moving With Different Speeds

不同移动速度的马尔可夫链混合模型估计

This article considers a new mixture of time-homogeneous finite Markov chains where the mixing is on the rate of movement and develops the EM algorithm for maximum likelihood estimation of the parameters of the mixture. Continuous- and discrete-time versions of the mixture are defined, and their estimation is considered separately. The developed methods are illustrated with an application to modeling bond ratings migration. The class of mixture models proposed in this…

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A Penalized Nonparametric Maximum Likelihood Approach to Species Richness Estimation

物种丰富度估计的惩罚非参数最大似然方法

We propose a class of penalized nonparametric maximum likelihood estimators (NPMLEs) for the species richness problem. We use a penalty term on the likelihood because likelihood estimators that lack it have an extreme instability problem. The estimators are constructed using a conditional likelihood that is simpler than the full likelihood. We show that the full-likelihood NPMLE solution given by Norris and Pollock can be found (with great accuracy) by using an appropriate…

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The Profile Sampler

剖面似然采样器

We consider frequentist inference for the parametric component θ separately from the nuisance parameter η in semiparametric models based on sampling from the posterior of the profile likelihood. We prove that this procedure gives a first-order–correct approximation to the maximum likelihood estimator and consistent estimation of the efficient Fisher information for θ, without computing derivatives or using complicated numerical approximations. An exact Bayesian…

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Inference for a Class of Transformed Hazards Models

一类变换风险率模型的统计推断

A new class of transformed hazard rate models is considered that contains both the multiplicative hazards model and the additive hazards model as special cases. The sieve maximum likelihood estimators are derived for the model parameters, and the estimators for the regression coefficients are shown to be consistent and asymptotically normal with variance achieving the semiparametric efficiency bound. Simulation studies are conducted to examine the small-sample properties of…

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Consistent Estimation with a Large Number of Weak Instruments

大量弱工具变量下的一致估计

This paper analyzes the conditions under which consistent estimation can be achieved in instrumental variables (IV) regression when the available instruments are weak and the number of instruments, Kn, goes to infinity with the sample size. We show that consistent estimation depends importantly on the strength of the instruments as measured by rn, the rate of growth of the so-called concentration parameter, and also on Kn. In particular, when Kn→∞, the concentration…

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A multi‐level panel STAR model for US manufacturing sectors

美国制造业部门的多层面板平滑转换自回归模型

Abstract We introduce a multi‐level smooth transition model for a panel of time series, which can be used to examine the presence of common nonlinear business cycle features across many variables. The model is positioned in between a fully pooled model, which imposes such common features, and a fully heterogeneous model, which allows for unrestricted nonlinearity. We introduce a second‐stage model linking the parameters that determine the timing of the switches between…

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Semiparametric three‐step estimation methods for simultaneous equation systems

联立方程系统的半参数三步估计方法

Abstract This paper proposes a new method for estimating a structural model of labour supply in which hours of work depend on (log) wages and the wage rate is considered endogenous. The main innovation with respect to other related estimation procedures is that a nonparametric additive structure in the hours of work equation is permitted. Though the focus of the paper is on this particular application, a three‐step methodology for estimating models in the presence of the…

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