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扩散过程的非参数估计及其在短期利率模型中的应用AI 解读

In this paper, we propose a nonparametric identification and estimation procedure for an ltd diffusion process based on discrete sampling observations. The nonparametric kernel estimator for the diffusion function developed in this paper deals with general ltd diffusion processes and avoids any functional form specification for either the drift function or the diffusion function. It is shown that under certain regularity conditions the nonparametric diffusion function…

半参数加性风险模型的拟合优度检验AI 解读

Kolmogorov-Smirnov and Cramér-von Mises type test statistics based on the standardised cumulative hazard process are proposed. It is very difficult to evaluate their asymptotic distributions, but they can be approximated by the use of the bootstrap. The advantages of the goodness-of-fit test are that arbitrary partitions of the time axis and covariate spaces are not needed for evaluating test statistics and that it has excellent consistency properties. The test is applied to…

基于病例—对照数据的 Logistic 回归拟合优度检验AI 解读

We test the logistic regression assumption under a case-control sampling plan. After reparameterisation, the assumed logistic regression model is equivalent to a two-sample semiparametric model in which the log ratio of two density functions is linear in data. By identifying this model with a biased sampling model, we propose a Kolmogorov-Smirnov-type statistic to test the validity of the logistic link function. Moreover, we point out that this test statistic can also be…

含协变量测量误差的病例对照研究贝叶斯半参数模型AI 解读

We develop a model and a numerical estimation scheme for a Bayesian approach to inference in case-control studies with errors in covariables. The model proposed in this paper is based on a nonparametric model for the unknown joint distribution for the missing data, the observed covariates and the proxy. This nonparametric distribution defines the measurement error component of the model which relates the missing covariates X with a proxy W. The oxymoron ‘nonparametric Bayes’…

生存数据的半参数贝叶斯分析AI 解读

This review article investigates the potential of Bayes methods for the analysis of survival data using semiparametric models based on either the hazard or the intensity function. The nonparametric part of every model is assumed to be a realization of a stochastic process. The parametric part, which may include a regression parameter or a parameter quantifying the heterogeneity of a population, is assumed to have a prior distribution with possibly unknown hyperparameters.…

广义半线性模型的有效估计AI 解读

The generalized semilinear model (GSLIM) extends the generalized linear model by allowing the addition of an unknown smooth function to the predictor parameter, producing a semiparametric model. Some previously proposed score-based estimators for the parametric component in this model are not √n consistent. We propose efficient estimators for both the parametric and nonparametric components of the GSLIM. The estimator for the parametric component is the solution to an…

生物尺寸关系的断裂：含测量误差的截断半参数回归AI 解读

Biological size relationships (i.e., regression of one size variable on another) are typically monotone but often break down at extreme values of the variables. Here we study the way in which a plant's biomass is apportioned to reproductive and other life activities. Working with a theory proposed by Weiner (1988) based an analogy between a biological plant and an industrial plant leads to a truncated regression model formulation. We consider a dataset involving 542…

包含空间协变量的鱼类物种丰富度分析AI 解读

Legislation passed in 1990 reducing the allowable sulfur dioxide emission levels in the United States is expected to reduce acidity in the Adirondack region of New York State. The number of fish species in a lake (species richness) depends on a number of physical and chemical factors, including the area, elevation, and acidity of the lake. Data on these and other factors are available for 1,166 Adirondack lakes. The data are analyzed with the goal of quantifying the effects…

广义半线性模型的有效估计量AI 解读

The generalized semilinear model (GSLIM) extends the generalized linear model by allowing the addition of an unknown smooth function to the predictor parameter, producing a semiparametric model. Some previously proposed score-based estimators for the parametric component in this model are not √n consistent. We propose efficient estimators for both the parametric and nonparametric components of the GSLIM. The estimator for the parametric component is the solution to an…

生物体大小关系的失效：含测量误差的截断半参数回归AI 解读

Biological size relationships (i.e., regression of one size variable on another) are typically monotone but often break down at extreme values of the variables. Here we study the way in which a plant's biomass is apportioned to reproductive and other life activities. Working with a theory proposed by Weiner (1988) based an analogy between a biological plant and an industrial plant leads to a truncated regression model formulation. We consider a dataset involving 542…

摘要暂缺

依赖指数半参数估计量收敛速率的说明AI 解读

Considerable recent attention has been devoted to semiparametric estimation of the dependence index, or the Hurst constant, using methods based on information in either frequency or time domains. Convergence rates of estimators in the frequency domain have been derived, and in the present paper we obtain them for estimators in the time domain. It is shown that the latter can have superior performance for moderate-range time series, but are inferior in the context of…

半参数似然比推断AI 解读

Likelihood ratio tests and related confidence intervals for a real parameter in the presence of an infinite dimensional nuisance parameter are considered. In all cases, the estimator of the real parameter has an asymptotic normal distribution. However, the estimator of the nuisance parameter may not be asymptotically Gaussian or may converge to the true parameter value at a slower rate than the square root of the sample size. Nevertheless the likelihood ratio statistic is…

具有序贯矩限制的面板数据模型的有效估计AI 解读

This paper considers asymptotically efficient estimation of the panel data models with sequential moment restrictions in an environment with i.i.d. observations. It is shown that the GMM estimator with an increasing set of instruments attains the semiparametric efficiency bound of the model. The estimator considered here allows for the heteroscedasticity of the unknown form.

一种半参数最大似然估计量AI 解读

A maximum likelihood estimator for models containing nuisance parameters is proposed. The estimator is shown to be asymptotically normal and attain the semiparametric efficiency bounds for a number of important econometric models. The idea is to find a parametric model that passes through the true model. The score for the parametric model is then estimated nonparametrically and the estimator is obtained by setting the estimated score to zero.

嵌套病例对照研究分析的伪似然方法AI 解读

In nested case-control studies the controls are sampled from the risk set at the failure times of the cases. The analytical basis for such studies has been limited to semiparametric estimators under proportional-hazard models. In this paper it is observed that conditional inclusion probabilities of ever being included in the nested case-control study can be obtained, where conditioning is on the information needed to carry out a nested case-control study. The inclusion…

传递泛函与半参数回归模型AI 解读

A general approach to semiparametric regression model construction is proposed, using the notation of a transfer functional. Estimators of unknown regression parameters are proposed, generalising the estimators of the parameters of the proportional hazards and the additive risk models.

多元失效时间分析中的风险比与交叉比回归AI 解读

Cox model marginal survivor function and pairwise correlation models are specified for a multivariate failure time vector. The corresponding mean and covariance structure for the cumulative baseline hazard variates and standard baseline hazard function estimators are used to develop joint estimating equations for hazard ratio and correlation parameters, in the absence of censorship. Semiparametric models for pairwise survivor functions are required to generalise these…

协变量缺失回归中的加权半参数估计AI 解读

This article investigates estimation of the regression coefficients in an assumed mean function when covariates on some subjects are missing. We examine the performance of a Horvitz and Thompson (1952)-type weighted estimator by using different estimates of the selection probabilities, which may be treated as nuisance parameters (or a nuisance function). In particular, we investigate the properties of the estimate of the regression parameters when the selection probabilities…

门槛计数回归的半参数估计及 Medicaid 服务利用应用AI 解读

This paper develops a semi-parametric estimation method for hurdle (two-part) count regression models. The approach in each stage is based on Laguerre series expansion for the unknown density of the unobserved heterogeneity. The semi-parametric hurdle model nests Poisson and negative binomial hurdle models, which have been used in recent applied literature. The empirical part of the paper evaluates the impact of managed care programmes for Medicaid eligibles on utilization…

门槛计数回归模型的半参数估计及Medicaid医疗利用应用AI 解读

This paper develops a semi-parametric estimation method for hurdle (two-part) count regression models. The approach in each stage is based on Laguerre series expansion for the unknown density of the unobserved heterogeneity. The semi-parametric hurdle model nests Poisson and negative binomial hurdle models, which have been used in recent applied literature. The empirical part of the paper evaluates the impact of managed care programmes for Medicaid eligibles on utilization…

时间序列模型中的自适应估计AI 解读

In a framework particularly suited for many time-series models we obtain a LAN result under quite natural and economical conditions. This enables us to construct adaptive estimators for (part of) the Euclidean parameter in these semiparametric models. Special attention is directed to group models in time series with the important subclass of models with time varying location and scale. Our set-up is confronted with the existing literature and, as examples, we reconsider…

平均导数分位数回归AI 解读

For fixed $\alpha \epsilon (0, 1)$, the quantile regression function gives the $\alpha$th quantile $\theta_{\alpha}(\mathbf{x})$ in the conditional distribution of a response variable Y given the value $\mathbf{X} = \mathbf{x}$ of a vector of covariates. It can be used to measure the effect of covariates not only in the center of a population, but also in the upper and lower tails. A functional that summarizes key features of the quantile specific relationship between X and…

加速失效时间模型的一类半参数回归方法AI 解读

In this paper a general class of nonparametric test statistics, which includes both linear and nonlinear rank tests for the accelerated failure time model, is inverted into estimating equations for multiple regression. For right-censored data this general class of semiparametric regression procedures includes the linear rank estimators of Tsiatis (1990), extends the Theil-Sen estimator based on Kendall's τ to multiple regression, and introduces several new families of…