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摘要暂缺

含 I(2) 过程的协整系统估计AI 解读

This paper considers the properties of systems likelihood procedures for cointegrated systems when the I(2) variables are present. Two alternative methods are proposed: one is based on the full system likelihood, whereas another is based on the subsystem likelihood. By eliminating all unit roots in the system by the use of prior information concerning the presence of unit roots, these procedures yield estimates whose asymptotic distributions are mixed normal, free from…

联立方程系统中的多变量广义 ARCHAI 解读

This paper presents theoretical results on the formulation and estimation of multivariate generalized ARCH models within simultaneous equations systems. A new parameterization of the multivariate ARCH process is proposed, and equivalence relations are discussed for the various ARCH parameterizations. Constraints sufficient to guarantee the positive definiteness of the conditional covariance matrices are developed, and necessary and sufficient conditions for covariance…

非正则最大似然问题AI 解读

SUMMARY Four non-regular estimation problems are reviewed and discussed. One (the unbounded likelihood problem) involves distributions with infinite spikes, for which maximum likelihood can fail to give consistent estimators. A comparison is made with modified likelihood and spacings methods which do give efficient estimators in this case. An application to the Box–Cox shifted power transform is given. The other three problems occur when the true parameter lies in some…

通货膨胀率的长记忆：国际证据AI 解读

The authors examine monthly inflation rates of five industrial countries. The application of tests against stationarity as well as tests against a unit root yield contradictory results. Thus, fractional integration allowing for long memory is a plausible model. The authors discuss and apply the periodogram regression in order to estimate the difference parameters. For all countries, the authors find estimates significantly different from one as well as from zero. This is…

GARCH(1,1) 与 IGARCH(1,1) 最大似然估计量的有限样本性质：蒙特卡洛考察AI 解读

This paper compares GARCH(1,1) and IGARCH(1,1) models via a Monte Carlo study of the finite sample properties of the maximum likelihood estimator and related test statistics. While the asymptotic distribution is well approximated by the estimated t statistics, other commonly used statistics do not behave as well. In addition, the estimators themselves are skewed in small samples. For the null hypothesis of IGARCH(1,1), Wald tests typically have the best size while the…

基于 p* 公式的简化预测密度AI 解读

The predictive density proposed by Harris (1989) is based on integrating the density for a new observation with respect to the estimated sampling distribution of the maximum likelihood estimator of the unknown parameter. This has good properties, but is rather complicated to compute even for simple models. An approximation to the Harris proposal is considered which consists of approximating the sampling distribution of the maximum likelihood estimator of the unknown…

多元二元响应的边际回归分析AI 解读

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…

不完整更新过程数据的非参数最大似然估计AI 解读

The problem of estimating the lifetime distribution based on data from independently and identically distributed stationary renewal processes is addressed. The data are incomplete. A nonparametric maximum likelihood estimate of the Lifetime distribution is derived using the em algorithm. The missing information principle is used to estimate the standard error of the estimated distribution. The methodology is applied to a problem in the nursing profession where nurses…

区间删失观测下马尔可夫疾病—死亡过程的非参数估计AI 解读

The nonparametric estimation of the cumulative transition intensity functions in a threestate time-nonhomogeneous Markov process with irreversible transitions, an ‘illness-death’ model, is considered when times of the intermediate transition, e.g. onset of a disease, are interval-censored. The times of ‘death’ are assumed to be known exactly or to be right-censored. In addition the observed process may be left-truncated. Data of this type arise when the process is sampled…

摘要暂缺

一般估计函数的近似似然比AI 解读

The method of estimating functions (Godambe, 1991) is commonly used when one desires to conduct inference about some parameters of interest but the full distribution of the observations is unknown. However, this approach may have limited utility, due to multiple roots for the estimating function, a poorly behaved Wald test, or lack of a goodness-of-fit test. This paper presents approximate likelihood ratios that can be used along with estimating functions when any of these…

共同典型变量AI 解读

Canonical correlation analysis measures the linear relationship between two random vectors X1 and X2 as the maximum correlation between linear combinations of X1 and linear combinations of X2. Several generalisations of canonical correlation analysis to k2 random vectors X1 …, Xk have been proposed in the literature (Kettenring, 1971, 1985), based on the principle of maximising some generalised measure of correlation. In this paper we propose an alternative generalisation,…

多响应回归模型的曲率度量AI 解读

The Bates & Watts (1981) curvature measures developed for single response nonlinear least squares problems are extended to multiresponse parameter estimation problems based on the Box-Draper estimation criterion. Exact determination contours are approximated by contours of the generalised least squares model conditioned on the maximum likelihood estimate of the covariance matrix for the responses. By this approximation, curvature measures calculated for the generalised least…

部分删失数据下的最大似然估计AI 解读

Suppose one observes independent samples of size $n$ from both the mixture density $\int p(x \mid z) d\eta(z)$ and from the distribution $\eta$. The kernel $p(x \mid z)$ is known. We show asymptotic normality and efficiency of the maximum likelihood estimator for $\eta$.

隐马尔可夫模型的一致且渐近正态参数估计AI 解读

Hidden Markov models are today widespread for modeling of various phenomena. It has recently been shown by Leroux that the maximum-likelihood estimate (MLE) of the parameters of a such a model is consistent, and local asymptotic normality has been proved by Bickel and Ritov. In this paper we propose a new class of estimates which are consistent, asymptotically normal and almost as good as the MLE.

正电子发射断层成像中极大似然估计的渐近一致性及应用AI 解读

This paper indicates that a minor modification of the maximum likelihood estimate of Vardi, Shepp and Kaufman can be regarded as a step in the standard nonparametric MLE by the method of sieves and establishes the asymptotic consistency for it. This method of sieves suggests that the number of pixels needs to be in line with the number of detectors in order to avoid poor image reconstructions. A simulation study is also presented to support this suggestion.

协方差函数的非参数估计AI 解读

We describe kernel methods for estimating the covariance function of a stationary stochastic process, and show how to ensure that the estimator has the positive semidefiniteness property. From a practical viewpoint, our method is significant because it does not demand a parametric model for covariance. From a technical angle, our results exhibit a striking departure from those in more familiar cases of kernel estimation. For example, in the context of covariance estimation,…

受约束 M 估计的渐近理论AI 解读

Limit theorems for an $M$-estimate constrained to lie in a closed subset of $\mathbb{R}^d$ are given under two different sets of regularity conditions. A consistent sequence of global optimizers converges under Chernoff regularity of the parameter set. A $\sqrt n$-consistent sequence of local optimizers converges under Clarke regularity of the parameter set. In either case the asymptotic distribution is a projection of a normal random vector on the tangent cone of the…

相干可靠性系统中的竞争风险：参数情形下的估计AI 解读

A coherent reliability system is a machine composed of a number of components that fails as soon as the set of failed components reaches certain fatal set-thresholds. On failure of the machine, an autopsy report reveals its time of failure and the set of failed components. I use incomplete data methods to obtain maximum likelihood estimates of parameters characterizing the lifetime distributions of the components, based on a sample of autopsy reports.

比例风险模型的分组持续时间分析：最小卡方估计与设定检验AI 解读

This article develops a semiparametric, minimum chi-squared estimation method of the proportional hazard model for the case when durations are grouped and covariates are categorical. The proposed estimator is easy to compute, yet asymptotically as efficient as the maximum likelihood estimator. This article also suggests simple specification tests for the proportional hazard model. If proportionality holds, then two sets of minimum chi-squared estimators, one from a further…

相干可靠性系统中的竞争风险：参数情形的估计AI 解读

A coherent reliability system is a machine composed of a number of components that fails as soon as the set of failed components reaches certain fatal set-thresholds. On failure of the machine, an autopsy report reveals its time of failure and the set of failed components. I use incomplete data methods to obtain maximum likelihood estimates of parameters characterizing the lifetime distributions of the components, based on a sample of autopsy reports.

分组持续期比例风险模型：最小卡方估计与设定检验AI 解读

This article develops a semiparametric, minimum chi-squared estimation method of the proportional hazard model for the case when durations are grouped and covariates are categorical. The proposed estimator is easy to compute, yet asymptotically as efficient as the maximum likelihood estimator. This article also suggests simple specification tests for the proportional hazard model. If proportionality holds, then two sets of minimum chi-squared estimators, one from a further…

通过条件化近似消除干扰参数AI 解读

The general problem of inference about a scalar parameter of interest θ in the presence of a nuisance parameter λ using conditional inference is considered.xml . A condition is given under which inference based on the conditional distribution of θ^, the maximum likelihood estimate of θ, given λ^o, the maximum likelihood estimate of λ for fixed θ = θ0, is optimal, in a certain sense. When this condition is not satisfied, it is shown that inference should be based on the…