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A Comparison between Maximum Likelihood and Generalized Least Squares in a Heteroscedastic Linear Model

异方差线性模型中最大似然与广义最小二乘的比较

We consider a linear model with normally distributed but heteroscedastic errors. When the error variances are functionally related to the regression parameter, one can use either maximum likelihood or generalized least squares to estimate the regression parameter. We show that likelihood is more sensitive to small misspecifications in the functional relationship between the error variances and the regression parameter.

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Two-Sample Repeated Significance Tests Based on the Modified Wilcoxon Statistic

基于修正 Wilcoxon 统计量的两样本重复显著性检验

The asymptotic distribution theory of sequentially computed modified-Wilcoxon scores is developed for two-sample survival data with random staggered entry and random loss to follow-up. The asymptotic covariance indicates generally dependent modified-Wilcoxon increments, contradicting (the authors' reading of) Jones and Whitehead (1979). A repeated significance testing procedure is presented for testing the equality of two survival distributions based on the asymptotic…

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The Effect of Two-Stage Sampling on Ordinary Least Squares Methods

两阶段抽样对普通最小二乘方法的影响

We look at the effect of intracluster correlation on standard procedures in linear regression. The ordinary least squares estimator, , of the coefficient vector performs well in most cases but the usual estimator of cov() and procedures based on this such as confidence intervals and hypothesis tests can be seriously misleading. The size of the effect, however, tends to be smaller than the corresponding effect on the variance of an estimated mean in two-stage sampling…

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Cluster Inference by using Transitivity Indices in Empirical Graphs

利用经验图传递性指标进行聚类推断

A random graph model is introduced for similarities observed between the objects sampled from an unknown cluster structure. We investigate this model and show how some common transitivity indices in empirical graphs can be used for making statistical inferences about cluster structures.

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An Inconsistent Maximum Likelihood Estimate

一个不一致的最大似然估计

An example is given of a family of distributions on [— 1, 1] with a continuous one-dimensional parameterization that joins the triangular distribution (when Θ = 0) to the uniform (when Θ = 1), for which the maximum likelihood estimates exist and converge strongly to Θ = 1 as the sample size tends to infinity, whatever be the true value of the parameter. A modification that satisfies Cramér's conditions is also given.

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The Powers and Strengths of Tests for Multinomials and Contingency Tables

多项分布与列联表检验的功效及加权功效

The strength of a significance test is defined as a weighted average of the power especially if the weights are a prior density. The concept is a compromise between Neyman-Pearsonian and Bayesian methods and is applied to tests for multinomial equiprobability and for no association in contingency tables. The differences of the power functions of two criteria, X 2 and G, are illustrated for the trinomial, where G arose earlier from a partially Bayesian approach. Other methods…

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The Effects of Asymmetric Filters on Seasonal Factor Revisions

非对称滤波器对季节因子修订的影响

Recent data seasonally adjusted by moving average methods are subject to revisions due to differences in the properties of the linear filters for the same seasonal adjustment when later data become available. This article introduces a measure of the total revision associated with the concurrent and forecasting seasonal filters and applies it to the Census Method II-X-11 variant and the X-11-ARIMA method. To consider the fact that the spectrum of many economic indicators…

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Estimation of Nonlinear Learning Models

非线性学习模型的估计

The article develops the structure and estimates the parameters of a nonlinear learning model applicable to research designs in which students are tested at the beginning and end of a course of study. A student's precourse score is an error-ridden proxy for his precourse aptitude. As a remedy for this problem, the article combines a probit model of test score outcomes, a learning function, and a linear equation relating aptitude to demographic characteristics to deduce the…

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Round Robin Analysis of Variance via Maximum Likelihood

基于最大似然的循环配对方差分析

A class of two-way random-effects models is presented for analyzing data that arise in a large variety of round robin designs. Examples of such designs can be found in numerous games, tournaments, and social interactions. The proposed models provide information not only about individual differences but also about the mutual contingency of the behaviors of interaction dyads. The statistical inference of the linear effects is discussed and a converging algorithm based on the…

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On Sample-Size Selection and the Evaluation of Discriminability in the Model Choice Problem

模型选择中的样本量选择与可区分性评估

In this article we present a general Bayesian approach to discrimination. We describe how the difference between two separate families of distributions can be assessed in terms of differences between two binomial models. Two examples that illustrate the methodology are included. Specifically, we investigate the extent to which it is possible to discriminate between the von Mises and the wrapped normal distributions and also between the normal and a family of t distributions.

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Inference Based on Simple Rank Step Score Statistics for the Location Model

基于简单秩阶梯得分统计量的位置模型推断

A class of estimation procedures that are robust, relatively efficient, and yet computationally simple is proposed for the one- and two-sample location problems. Particular emphasis is placed on the problem of determining confidence intervals, a topic that has seen limited exposure in the literature. As a by-product, some interesting point estimates are obtained. A class of score functions that are ordinary step functions is considered for the location model. Point estimates…

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Estimating Latent Variable Systems When Specification is Uncertain: Generalized Component Analysis and the Eliminant Method

设定不确定时的潜变量系统估计:广义成分分析与消元法

This article argues that, to relieve the specification difficulties that frequently accompany latent variable models, a first application should in most cases employ an estimator that makes no assumption about the nature of the unobservables. The two possibilities are generalized component analysis, with the unobservables treated as incidental parameters; and the eliminant method, where they are removed by transformation of the model before estimation. It is shown that these…

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An Inconsistent Maximum Likelihood Estimate

一个不一致的最大似然估计

An example is given of a family of distributions on [— 1, 1] with a continuous one-dimensional parameterization that joins the triangular distribution (when Θ = 0) to the uniform (when Θ = 1), for which the maximum likelihood estimates exist and converge strongly to Θ = 1 as the sample size tends to infinity, whatever be the true value of the parameter. A modification that satisfies Cramér's conditions is also given.

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The Effects of Asymmetric Filters on Seasonal Factor Revisions

非对称滤波器对季节因子修订的影响

Recent data seasonally adjusted by moving average methods are subject to revisions due to differences in the properties of the linear filters for the same seasonal adjustment when later data become available. This article introduces a measure of the total revision associated with the concurrent and forecasting seasonal filters and applies it to the Census Method II-X-11 variant and the X-11-ARIMA method. To consider the fact that the spectrum of many economic indicators…

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Estimation of Nonlinear Learning Models

非线性学习模型的估计

The article develops the structure and estimates the parameters of a nonlinear learning model applicable to research designs in which students are tested at the beginning and end of a course of study. A student's precourse score is an error-ridden proxy for his precourse aptitude. As a remedy for this problem, the article combines a probit model of test score outcomes, a learning function, and a linear equation relating aptitude to demographic characteristics to deduce the…

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Bayesian Optimization of the Estimation of the Age Composition of a Fish Population

鱼类种群年龄构成估计的贝叶斯优化

To estimate the age distribution of a fish population, a two-phase stratified sample design is proposed. Bayesian methods are employed to determine (a) optimal estimators of the desired population proportions; and (b) the optimal choice of second-phase sample sizes subject to a fixed budget. A summary of the results of some numerical examples is presented. These examples demonstrate typical expected gains obtained by using the Bayesian optima as compared to alternative…

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Censoring and Stochastic Integrals.

删失与随机积分

A.2. On constructing a stochastic basis A.3.Proof of Theorem 2.3.4.• A.4. Proof of Lemma 3.2.1 . . . .A.5. Asymptotic normality of an estimator of mean lifetime.A.6.Proof of a theorem of Daniels.P.EFERENCES .

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