论文检索

三角矩最大似然估计及不完整生存信息分析AI 解读

A procedure is derived for computing maximum likelihood estimates from the sample trigonometric moments. Several examples are given which demonstrate the convenience of this hybrid approach. The Zippin-Armitage method for dealing with incomplete survival information is generalized. A simple expression is obtained for the survival curve given nonparametric estimators of (1) the probability density of survival times for patients who have died, and (2) the probability density…

自相关误差下非线性最小二乘与最大似然估计的小样本性质AI 解读

Rao and Griliches (1969) compared several methods of parameter estimation in models having autocorrelated errors. They concluded that nonlinear least squares estimators were not superior to two-stage linear estimators. This study partially replicates the Rao and Griliches Monte Carlo simulation and, in addition, examines the maximum likelihood estimator as a possible competitor. The simulation results are not consistent with those of Rao and Griliches; the small-sample…

对Schlesselman所提变换准则的评论AI 解读

In the two-way analysis of variance with replicates, Schlesselman (1973) proposed a criterion of transformation based on classical statistics for testing homoscedasticity and additivity. He compared his criterion (Z(γ)) for selecting a transformation with the maximum likelihood estimate of Box and Cox (1964), and found Z(γ) superior in selecting a “correct” transformation when tested on models with normal and Cauchy error terms. We report here corrections of some of the…

参数函数与计量模型结构系数的最小期望损失估计AI 解读

Further sampling properties of previously derived (Zellner 1975) MELO estimates for reciprocals and ratios of parameters and for structural coefficients of econometric models are presented. Approximate small-sample moments and risk functions of MELO estimators for these problems are derived and compared with those of other well-known estimators. The exact finite sample distribution of the MELO reciprocal mean estimator is derived and compared with that of the maximum…

三角矩极大似然估计及其在不完整生存信息中的应用AI 解读

A procedure is derived for computing maximum likelihood estimates from the sample trigonometric moments. Several examples are given which demonstrate the convenience of this hybrid approach. The Zippin-Armitage method for dealing with incomplete survival information is generalized. A simple expression is obtained for the survival curve given nonparametric estimators of (1) the probability density of survival times for patients who have died, and (2) the probability density…

摘要暂缺

随机过程参数后验分布的渐近正态性AI 解读

Summary Asymptotic normality of the posterior distribution of a parameter in a stochastic process is shown to hold under conditions which do little more than ensure consistency of a maximum likelihood estimator. Much more stringent conditions are required to ensure asymptotic normality of the MLE. This contrast, which has implications of considerable significance, does not emerge in the classical context of independent and identically distributed observations.

基于删失数据的贝叶斯非参数估计AI 解读

Let $X_1, \cdots, X_n$ be a random sample from an unknown $\operatorname{cdf} F$, let $y_1, \cdots, y_n$ be known real constants, and let $Z_i = \min(X_i, y_i), i = 1, \cdots, n$. It is required to estimate $F$ on the basis of the observations $Z_1, \cdots, Z_n$, when the loss is squared error. We find a Bayes estimate of $F$ when the prior distribution of $F$ is a process neutral to the right. This generalizes results of Susarla and Van Ryzin who use a Dirichlet process…

具有自回归移动平均误差的随机线性差分方程的极大似然估计AI 解读

A method is proposed for the estimation of a general class of scalar linear time series models. The model takes the form of a stochastic difference equation for the dependent variable with exogenous variable inputs, and the disturbances are autocorrelated through an autoregressive moving average process. In the present paper an asymptotically efficient yet computationally simple estimation procedure (in the time domain) is derived for this model. The resulting estimator is…

协方差结构分析中的约束估计AI 解读

In covarianoe structure analysis, the method of weighted least squares for estimating parameters that are subject to functional constraints is developed. Statistical properties of the estimator are studied and a goodness-of-fit statistic is presented. Based on the penalty function technique, an algorithm is developed. This algorithm is able to produce not only the constrained weighted least squares estimator but also the constrained maximum likelihood estimator, if we choose…

类间相关系数的最大似然估计AI 解读

The method of maximum likelihood is used to estimate a mother-child correlation, ρMS, when there are a variable number of offspring per family. The technique is iterative and uses standard Newton-Raphson procedures to facilitate convergence. A comparison is made using Monte Carlo methods between the maximum likelihood estimator and other more traditional estimators of interclass correlations. It is shown that the maximum likelihood estimator is roughly equivalent in mean…

天气实验的若干分析方法AI 解读

Using generalized densities, maximum likelihood and ancillarity, methods are developed for the analysis of randomized weather modification experiments that incorporate predictor variables. The linear logistic form is used to model the distributional singularity at the origin, while a gamma model with predictors is developed for the component conditional on the presence of precipitation. Connexions between the component submodels are explored and illustrated using an…

基于伴随次序统计量的删失二元正态分布推断AI 解读

For a censored sample from a bivariate normal distribution consisting of the firstk ofn order statistics of one variable and the induced order statistics of the other variable, the maximum likelihood estimators of the parameters and the associated large sample co-variance matrix are derived. The likelihood ratio test for independence is also given and its power properties studied. These methods are useful in selection problems or in life testing situations in which…

家庭疾病数据的参数估计程序AI 解读

A procedure is proposed for estimating a parameter of an epidemic model from household data. The procedure is essentially a method of moments for martingales. It is computationally convenient and is less restrictive in its model assumptions than the maximum likelihood methods used so far. The approach is illustrated with measles data and is also shown to be useful when households contain susceptibles of different types.

多元自回归移动平均模型的精确似然函数AI 解读

By making use of the properties of tensor products, this paper describes the derivation of an expression for the exact likelihood function of a stationary process generated by a vector autoregressive-moving average model using concentrated maximum likelihood techniques. Furthermore, in the process of deriving the likelihood function, a closed form expression for the covariance function of the process in terms of the coefficients of the model is derived.

具有ARMA扰动的回归模型的最大似然估计AI 解读

The regression model with autoregressive-moving average disturbances may be cast in a form suitable for the application of Kalman filtering techniques. This enables the generalized least squares estimator to be calculated without evaluating and inverting the covariance matrix of the disturbances. The problem of forecasting future values of the dependent variable is also effectively solved when the Kalman filter technique is applied. Furthermore, the properties of the…

已知方差的若干多元正态模型中相关系数的简易最优渐近正态估计AI 解读

It is well-known that in certain multivariate normal models with known variances, maximum likelihood estimation of correlations is arithmetically cumbersome. For certain of these models, a relatively simple estimation technique based on the sufficient statistics is given and shown to be best asymptotically normal. The procedure uses the fact that many of the likelihood equations for these models are essentially cubic equations. A consistent, explicit solution for the…

方差分量的非负估计与预检验估计AI 解读

Nonnegative estimators of variance components involving preliminary tests are studied. The restricted maximum likelihood estimator and other truncated estimators may be viewed as preliminary test estimators. A new preliminary test estimator is proposed and studied. Recommendations of the levels of preliminary tests are made.

Logistic模型与潜在结构的估计AI 解读

Consider the logistic model for dichotomous response involving a group of individuals with varying levels of ability and a set of items with varying degrees of difficulty. This article is concerned with estimating the parameters of the latent ability distribution for any given group of individuals. An iterative procedure for obtaining maximum likelihood estimates of these parameters based on the missing information principle is presented and illustrated with real data. The…

正态混合分布与转换回归的估计AI 解读

Since the likelihood function corresponding to finite mixtures of normal distributions is unbounded, maximum likelihood estimation may break down in practice. The article introduces the “moment generating function estimator” defined as the estimator which minimizes the sum of squares of differences between the theoretical and sample moment generating functions. The consistency and asymptotic normality of the estimator are proved and its finite sample behavior is compared to…

Logistic回归与判别分析之间的选择AI 解读

Classifying an observation into one of several populations is discriminant analysis, or classification. Relating qualitative variables to other variables through a logistic cdf functional form is logistic regression. Estimators generated for one of these problems are often used in the other. If the populations are normal with identical covariance matrices, discriminant analysis estimators are preferred to logistic regression estimators for the discriminant analysis problem.…

扰动较小时有限信息极大似然估计量的改进AI 解读

The limited information maximum likelihood (LIML) estimator is shown to be inadmissible in terms of asymptotic expansions of the distributions of the estimators. The LIML estimator is improved by combining it linearly with the two-stage or the ordinary least squares estimator.

基于最大 k 个观测值的参数与极高分位数估计AI 解读

We consider an estimation problem when only the k largest observations of a sample of size n are available. It is assumed that the underlying distribution function F belongs to the domain of attraction of a known extreme-value distribution and that k remains fixed as n → ∞. We present estimators for the location and scale parameters and for p-quantiles of F, where p is of the form 1 — c/n (c fixed). These estimators are either asymptotically maximum likelihood or minimum…

混合分布的非参数极大似然估计AI 解读

The nonparametric maximum likelihood estimate of a mixing distribution is shown to be self-consistent, a property which characterizes the nonparametric maximum likelihood estimate of a distribution function in incomplete data problems. Under various conditions the estimate is a step function, with a finite number of steps. Its computation is illustrated with a small example.