论文检索

关于自然死亡率半参数估计量的一则札记AI 解读

A semiparametric estimator of natural mortality, introduced by Hearn, Sandland & Hampton (1987), was studied by Leigh (1988), who noted that its asymptotic variance may sometimes be infinite. We discuss the nonnorrnal asymptotic behaviour that can occur in this case, and remark on difficulties that it causes in practice.

一类半参数模型中实值参数的估计AI 解读

We study semiparametric models where for a fixed value of the finite-dimensional parameter there exists a sufficient statistic for the nuisance parameter. An asymptotically normal sequence of estimators for the parametric component is constructed, which is efficient under the assumption that projecting on the set of nuisance scores is equivalent to taking conditional expectations given the sufficient statistic. The latter property is checked for a number of examples, in…

半参数模型中的极小极大估计AI 解读

The statistical analysis of multidimensional data has been greatly influenced by the widespread use of computer-intensive smoothing techniques. These techniques allow one to look at the dependency of a response on several covariates without actually specifying the exact form of that dependency. Nevertheless, when the response's dependency on some subset of the covariates can be assumed to be, say, linear, common sense dictates incorporating this assumption into the…

半参数模型中的极小极大估计AI 解读

The statistical analysis of multidimensional data has been greatly influenced by the widespread use of computer-intensive smoothing techniques. These techniques allow one to look at the dependency of a response on several covariates without actually specifying the exact form of that dependency. Nevertheless, when the response's dependency on some subset of the covariates can be assumed to be, say, linear, common sense dictates incorporating this assumption into the…

多期条件矩限制所蕴含的效率界AI 解读

In this article we study a class of econometric models that imply a set of multiperiod conditional moment restrictions. These restrictions depend on an unknown parameter vector. We construct an extensive class of consistent, asymptotically normal estimators of this parameter vector and calculate the greatest lower bound for the asymptotic covariance matrices of estimators in this class. In so doing, we extend results reported by Hansen (1985) and Stoica, Söderström, and…

两样本广义优势率模型的估计与检验AI 解读

The generalized odds ratio for a survival variable T is defined as Λ T (t | c) = c -1[1 - Sc (t)]/Sc (t) for c > 0 and -log S(t) for c = 0, where S(t) = Pr(T > t). This ratio coincides with the integrated hazard for c = 0 and the odds ratio for c = 1. When the distribution of T depends on a covariate vector, we assume that conditionally on the covariates, log Λ T (t | c) is linear in the covariates. This model is a generalization of the proportional hazard model (PHM), which…

部分线性模型中的核平滑AI 解读

SUMMARY Kernel smoothing is studied in partial linear models, i.e. semiparametric models of the form yi=ξi′β+f(ti)+εi(1⩽i⩽n), where the ξi are fixed known p vectors, β is an unknown vector parameter and f is a smooth but unknown function. Two methods of estimating β and f are considered, one related to partial smoothing splines and the other motivated by partial residual analysis. Under suitable assumptions, the asymptotic bias and variance are obtained for both methods, and…

根号 N 一致的半参数回归AI 解读

One type of semiparametric regression is b8X A u(Z), where b and u(Z) are an unknown slope coefficient vector and function. Estimates of b based on incorrect parametrization of u are generally inconsist ent, whereas consistent nonparametric estimates converge slowly. An e stimate, bC, is constructed by inserting nonpar-ametric regression es timates in the nonlinear orthogonal projection on Z. Under regularity conditions bC is shown to be N1/2-consistent for b and…

最小距离泛函的“自动”稳健性AI 解读

The minimum distance (MD) functional defined by a distance $\mu$ is automatically robust over contamination neighborhoods defined by $\mu$. In fact, when compared to other Fisher-consistent functionals, the MD functional was no worse than twice the minimum sensitivity to $\mu$-contamination, and at least half the best possible breakdown point. In invariant settings, the MD functional has the best attainable breakdown point against $\mu$-contamination among equivariant…

半参数部分样条与广义样条模型中的参数零模型检验AI 解读

Cox and Koh (1986) considered the model $y_i = f(x(i)) + \varepsilon_i, \varepsilon_i$ i.i.d. $N(0, \sigma^2)$, with the (parametric) null hypothesis $f(x), x \in \lbrack 0, 1 \rbrack$, a polynomial of degree $m - 1$ or less, versus the alternative $f$ is "smooth," based on the Bayesian model for $f$ which leads to polynomial smoothing spline estimates for $f$. They showed that there was no uniformly most powerful test and found the locally most powerful (LMP) test. We…

半参数计量经济学：综述AI 解读

Abstract Semiparametric econometric models contain both parametric and nonparametric components, reflecting in some fashion what has been learned from economic theory and previous empirical experience, and what remains unknown. They raise such questions as how well the parametric component can be estimated, and how to construct rules of inference with good statistical properties. The paper attempts to survey the econometric and most relevant statistical literature on…

比例风险模型中中位与平均生存时间的估计及置信区间AI 解读

Estimation procedures and confidence intervals are given for the median and mean survival time in the proportional hazard regression model. For median survival, the methods apply to censored data. The procedures are based on Cox's partial likelihood estimates of the linear model parameters in the log linear proportional hazard model and on Breslow's estimate of the baseline hazard function. The asymptotic properties of these semiparametric estimates are developed and they…

密度估计的半参数方法AI 解读

One method of fitting a parametric density function f(x, θ) is first to estimate θ by maximum likelihood, say, and then to estimate f(x, θ) by . On the other hand, when the parametric model does not hold, the true density f(x) may be estimated nonparametrically, as in the case of a kernel estimate . The key idea proposed is to fit a combination of the parametric and nonparametric estimates, namely where π (0 ≤ π ≤ 1) is unknown. The parameter π is estimated from the data,…

泊松过程数据的回归方法AI 解读

This article is directed toward situations where individuals can experience repeated events, and data on an individual consist of the number and occurrence times of events, along with concomitant variables. Methods of regression analysis are presented, based on Poisson process and proportional intensity assumptions. These include parametric and semi-parametric approaches to model fitting, model assessment, and the treatment of random effects. In addition, insight is gained…

二元选择与删失回归模型中分布自由估计量的效率界AI 解读

We derive lower bounds on the asymptotic variances for regular distribution-free estimators of the parameters of the binary choice model and the censored regression (Tobit) model. A distribution-free (or semiparametric) estimator is one that does not require any assumption about the distribution of the stochastic error term in the model, apart from regularity conditions. For the binary choice model, we obtain an explicit lower bound for the asymptotic variance for the slope…

均值突变模型中的条件自助法AI 解读

Bootstrap methods are not inherently conditional, but they can be made so by appropriate stratification of the simulated samples which bootstrap produces. We show how stratification can work in a bootstrap analysis of mean-shift in Nile river flow data. The results are compared with both parametric and semiparametric likelihood analyses. The paper ends with some general remarks on conditional bootstraps.

基于二元面板数据的随机效应线性模型半参数分析AI 解读

Andersen_(1970) considered the problem of inference on random effects linear models from binary response panel data, and showed that inference is possible if the disturbances for each panel member are known to be white noise with the logistic distribution. The present paper shows that inference remains possible if the disturbances are known only to be time-stationary. A conditional version of the maximum score estimator consistently estimates the parameters up to scale.…

比例风险模型中生存时间中位数与均值的估计及置信区间AI 解读

Estimation procedures and confidence intervals are given for the median and mean survival time in the proportional hazard regression model. For median survival, the methods apply to censored data. The procedures are based on Cox's partial likelihood estimates of the linear model parameters in the log linear proportional hazard model and on Breslow's estimate of the baseline hazard function. The asymptotic properties of these semiparametric estimates are developed and they…

均值突变模型中的条件自助法AI 解读

Bootstrap methods are not inherently conditional, but they can be made so by appropriate stratification of the simulated samples which bootstrap produces. We show how stratification can work in a bootstrap analysis of mean-shift in Nile river flow data. The results are compared with both parametric and semiparametric likelihood analyses. The paper ends with some general remarks on conditional bootstraps.

半参数模型中的渐近有效估计AI 解读

A general method for the construction of asymptotically efficient estimates in semiparametric models is presented. It improves and modifies Bickel's (1982) construction of adaptive estimates and obtains asymptotically efficient estimates under conditions weaker than those in Bickel.

摘要暂缺

摘要暂缺

天气与售电量关系的半参数估计AI 解读

A nonlinear relationship between electricity sales and temperature is estimated using a semiparametric regression procedure that easily allows linear transformations of the data. This accommodates introduction of covariates, timing adjustments due to the actual billing schedules, and serial correlation. The procedure is an extension of smoothing splines with the smoothness parameter estimated from minimization of the generalized cross-validation criterion introduced by…

摘要暂缺