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基于最小消息长度估计的单因子分析AI 解读

SUMMARY The minimum message length (MML) technique is applied to the problem of estimating the parameters of a multivariate Gaussian model in which the correlation structure is modelled by a single common factor. Implicit estimator equations are derived and compared with those obtained from a maximum likelihood (ML) analysis. Unlike ML, the MML estimators remain consistent when used to estimate both the factor loadings and the factor scores. Tests on simulated data show the…

删失数据的最小 Hellinger 型距离估计AI 解读

A Hellinger-type distance for hazard rate functions is defined. It is used to obtain a class of minimum distance estimators for data that are subject to a possible right censorship. The corresponding score process is shown to be approximated by a martingale, which is exploited to obtain the asymptotic normality under considerably weaker conditions than those normally assumed for minimum Hellinger distance estimators. It is also shown that under the parametric assumption the…

混合分布的一致估计AI 解读

A maximum-penalized-likelihood method is proposed for estimating a mixing distribution and it is shown that this method produces a consistent estimator, in the sense of weak convergence. In particular, a new proof of the consistency of maximum-likelihood estimators is given. The estimated number of components is shown to be at least as large as the true number, for large samples. Also, the large-sample limits of estimators which are constrained to have a fixed finite number…

删失数据下尺度参数的最小距离估计AI 解读

This article examines how the level of censoring affects the performance of estimators of scale that minimize a weighted Cramérvon Mises distance between the Kaplan-Meier product-limit estimator of the survival distribution function and an assumed model. The article shows that under certain conditions these estimators are asymptotically normal if the survival function is a member of the assumed scale family. Weights that minimize the asymptotic variance under these…

多元 Probit 模型最大似然估计的存在性与唯一性AI 解读

The multivariate probit model (MPM) is a particular case of the class of correlated prediction models. A correlated prediction model is especially useful when prediction or classification is envisaged into diagnostic classes that are combinations of binary responses. The parameter vector consists of a “location” part and an “association” part. The location part accounts for the effect the regressors have on the marginal probabilities of the binary responses. The association…

聚类离散与连续结局的双变量潜变量模型AI 解读

We use the concept of a latent variable to derive the joint distribution of a continuous and a discrete outcome, and then extend the model to allow for clustered data. The model can be parameterized in a way that allows one to write the joint distribution as a product of a standard random effects model for the continuous variable and a correlated probit model for the discrete variable. This factorization suggests a convenient approach to parameter estimation using…

条件 Logit 的可推广表述与诊断方法AI 解读

The conditional logit model is a multinomial logit model that permits the inclusion of choice-specific attributes. This article shows that the conditional logit model will maximize entropy given a set of attribute-value preserving constraints. A correspondence between the maximum entropy (ME) and maximum likelihood (ML) estimates for logit probabilities is established. Some easily computable and useful diagnostics for logit analysis are provided, and it is shown that an…

混合模型的残差诊断AI 解读

A sample is commonly modeled by a mixture distribution if the observations follow a common distribution, but the parameter of interest differs between observations. For example, we observe the lengths but not the ages of a sample offish. It may be reasonable to assume that length is normally distributed about an unknown mean that depends on the age of the fish. Provided there is more than one age class in the sample, then the data are distributed as a mixture of normals. In…

重复测量实验中允许时间异方差的 ARMA 协方差结构AI 解读

Rochon and Helms (1989) presented a model for analyzing repeated measures experiments. The general linear model was used to assess the influence of covariate information, and ARMA time series models were put forward to characterize the covariance matrix among the repeated measures. Practical experience has suggested, however, that the ARMA assumption of constant variances and autocovariances over time is too restrictive for many applications. For example, observations may be…

次序统计量与推断：估计方法AI 解读

List of Tables. List of Figures. Introduction. Basic Theory. Moments and Other Expected Values. Linear Estimation Based on Order Statistics. Maximum Likelihood Estimation. Approximate Maximum Likelihood Estimation. Optimal Linear Estimation Based on Selected Order Statistics. Cohen -Whitten Estimators: Using Order Statistics.Estimation in Regression Models. A Sample Completion Technique for Censored Samples. Bibliography. Index.

删失数据的尺度最小距离估计AI 解读

This article examines how the level of censoring affects the performance of estimators of scale that minimize a weighted Cramérvon Mises distance between the Kaplan-Meier product-limit estimator of the survival distribution function and an assumed model. The article shows that under certain conditions these estimators are asymptotically normal if the survival function is a member of the assumed scale family. Weights that minimize the asymptotic variance under these…

摘要暂缺

定期观测三状态马尔可夫过程的非参数估计及艾滋病应用AI 解读

SUMMARY Estimation in a three-state Markov process with irreversible transitions in the presence of interval-censored data is considered. A nonparametric maximum likelihood procedure for the estimation of the cumulative transition intensities is presented. A self-consistent estimator of the parameters is defined and it is shown that the maximum likelihood estimator is a self-consistent estimator. This extends the idea of self-consistency introduced by Efron to the estimation…

半参数加性回归AI 解读

SUMMARY A simple estimator for β is proposed for the model y = x'β + g(t)+ error, g smooth but unknown. The approach is to approximate the estimating equation obtained from a ***semiparametric likelihood and in the simplest case reduces to minimizing the distance between the 'pseudoresiduals' y - x'β and a local linear cross-validated estimate of them. When the errors are independent with finite variance, the bias and variance of the estimate are computed and compared…

利用部分指数模型估计多元均值参数AI 解读

SUMMARY A class of partly exponential models is proposed for the regression analysis of multivariate response data. The class is parameterized in terms of the response mean and a general shape parameter. It includes the generalized linear error model and exponential dispersion models as special cases. Maximum likelihood equations for mean parameters are shown to be of the same form as certain generalized estimating equations, and maximum likelihood estimates of mean and…

依赖数据的受约束Monte Carlo最大似然估计AI 解读

SUMMARY Maximum likelihood estimates (MLEs) in autologistic models and other exponential family models for dependent data can be calculated with Markov chain Monte Carlo methods (the Metropolis algorithm or the Gibbs sampler), which simulate ergodic Markov chains having equilibrium distributions in the model. From one realization of such a Markov chain, a Monte Carlo approximant to the whole likelihood function can be constructed. The parameter value (if any) maximizing this…

广义矩估计竞争模型的非嵌套检验AI 解读

Non-nested tests are proposed for competing models estimated by generalized method of moments. Results are presented for non-nested linear regression models with het- eroskedasticity and serial correlation of unknown form and differing instrument validity assumptions. Regression forms of the statistics are also presented. THIS PAPER IS CONCERNED with providing a procedure whereby non-nested models estimated by generalized method of moments (GMM) (Hansen (1982)) may be com-…

摘要暂缺

让噪声数据发挥作用AI 解读

Maximum-likelihood estimators of production technologies are developed that deal with missing data and measurement errors, making alternative assumptions regarding the endogeneity of labor and missing data patterns. The estimators yield indices of the returns to scale, mean square deviation from the efficient frontier, and (when labor is treated as endogenous) mean square deviation from efficient factor mixes. To gauge the performance of the alternative estimators, they are…

评估利率期限结构的预期假说：协整向量分析AI 解读

The author tests cointegration restrictions that are consistent with the expectations hypothesis of the term structure by employing the full-information maximum likelihood methods developed by S. Johansen. Yield curves appear to be the result of cointegration among interest rates. The cointegration vectors that best describe the long-term impact of interest-rate levels on interest-rate changes can often be written as linear combinations of interest-rate spreads. There is,…

因子 GARCH 模型的替代估计量：蒙特卡洛比较AI 解读

Abstract This paper proposes four estimators for factor GARCH models: two‐stage univariate GARCH (2SUE), two‐stage quasi‐maximum likelihood (2SML), quasi‐maximum likelihood with known factor weights (RMLE), quasi‐maximum likelihood with unknown factor weights (MLE). A Monte‐Carlo study is designed for bivariate one‐factor GARCH models to examine the finite sample properties. Results are presented for biases, ratios of standard errors to standard deviations, ratios of…

随机乘法删失模型中经验分布的大样本研究AI 解读

Consider an incomplete data problem with the following specifications. There are three independent samples $(X_1, \ldots, X_m), (Z_1, \ldots, Z_n)$ and $(U_1, \ldots, U_n)$. The first two samples are drawn from a common lifetime distribution function $G$, while the third sample is drawn from the uniform distribution over the interval $(0,1)$. In this paper we derive the large sample properties of $\hat{G}_{m,n}$, the nonparametric maximum likelihood estimate of $G$ based on…

有限总体偏倚抽样下的非参数推断AI 解读

We consider a biased sampling model that has been found useful in incorporating size biases inherent in many types of discovery data. The model postulates that the data are obtained from a finite population by selecting successively without replacement and with probability proportional to some measure of size. Unlike the ppswor scheme in survey sampling, it is assumed here that the size measure is a function of the unknown population values. In this article, we consider…

利用代理结果数据与验证样本进行推断AI 解读

In the context of estimating β from the regression model Pβ(Y|X), relating response Y to covariates X, suppose that only a surrogate response S is available for most study subjects. Suppose that for a random subsample of the study cohort, termed the validation sample, the true outcome Y is available in addition to S. We consider maximum likelihood estimation of β from such data and show that it is nonrobust to misspecification of the distribution relating the surrogate to…