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The Selection of Terms in an Orthogonal Series Density Estimator

正交级数密度估计中的项选择

We show that Kronmal and Tarter's well-known rule for selecting the terms in an orthogonal series density estimator can lead to poor performance and even inconsistency in certain cases. These difficulties arise when the underlying density has a nonmonotone sequence of Fourier coefficients, as is likely to be the case with sharply peaked or multimodal distributions. We suggest a way of overcoming these shortcomings.

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The Equivalence of Regression-Simple and Best-Linear-Unbiased Estimators with Type II Censored Data from a Location Scale Distribution

位置—尺度分布Ⅱ型删失数据下简单回归与最佳线性无偏估计的等价性

This article gives necessary and sufficient conditions for the equivalence of the simple linear unbiased estimator (SLUE) and the best linear unbiased estimator (BLUE) of the parameters when there are k independent sources of Type II censored data from a location scale distribution in which the location parameter is an unknown linear function of certain given independent variables and the scale parameter is an unknown constant. It also shows that the BLUE can be obtained in…

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Likelihood Ratio Tests for a Change in the Multivariate Normal Mean

多元正态均值变化的似然比检验

A sequence of independent multivariate normal vectors with equal but possibly unknown variance matrices are hypothesized to have equal mean vectors, and we wish to test that the mean vectors have changed after an unknown point in the sequence. The likelihood ratio test is based on the maximum Hotelling T 2 for the sequences before and after the change point. The main result is a conservative approximation for its null distribution based on an improved Bonferroni inequality.…

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Combining Information on Measurement Error in the Errors-in-Variables Model

变量含误差模型中测量误差信息的组合

For the regression model in which an explanatory variable contains measurement error, the instrumental variable and the correction for attenuation estimators of slope are considered. Although each requires extra information that is rarely available in ideal form, examinations of asymptotic variances and simulation results suggest that the correction for attenuation performs as well as a fairly strong instrumental variable when the measurement errors are not too large, and…

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Further Developments on the Robustness of Clevenson—Zidek-Type Means Estimators

Clevenson–Zidek 型均值估计量稳健性的进一步研究

Tsui (1984) showed that many Clevenson—Zidek-type Poisson means estimators are better than the usual estimator under the normalized squared error loss (1.1), even when the underlying distributions are negative binomial. This article shows that this dominance result is still true when the underlying distributions belong to a much larger class of distributions. This class includes all mixtures of Poisson distributions, and hence the negative binomial result is a very special…

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Stabilizing Binomial n Estimators

二项分布试验次数参数估计的稳定化

The maximum likelihood estimator of the binomial parameter n can be highly unstable, resulting in huge fluctuations in the estimate when the data are only slightly perturbed. A method of assessing this sensitivity, based on perturbing the log-likelihood function, is proposed and examined.

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Robust Estimates for ARMA Models

ARMA 模型的稳健估计

Two new classes of robust estimates for ARMA models are introduced: estimates based on residual autocovariances (RA estimates), and estimates based on truncated residual autocovariances (TRA estimates). A heuristic derivation of the asymptotic normal distribution is given. We also perform a Monte Carlo study to compare the robustness properties of these estimates with the least squares, M, and GM estimates. In this study we consider observations that correspond to a Gaussian…

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Least Squares Regression When the Independent Variable Follows an ARIMA Process

自变量服从 ARIMA 过程时的最小二乘回归

In the regression model yt = α + βxt + ut where the disturbances ut may be autocorrelated and xt follows an ARIMA(p, 1, q) process, it is shown that the asymptotic distributions of the ordinary and generalized least squares estimates of β are identical.

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Asymptotic Theory of Overparameterized Structural Models

过度参数化结构模型的渐近理论

A theory of overparameterized structural models is presented. In such a model some “redundant” parameters are involved; the parameter vector is not identified, and the information matrix is not nonsingular. The minimum discrepancy function (MDF) test statistic is shown to have an asymptotic chi-squared distribution almost everywhere for a wide class of discrepancy functions. Asymptotic distribution properties of the MDF estimators are investigated. The factor analysis model…

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Time Series Model Specification in the Presence of Outliers

存在异常值时的时间序列模型设定

Outliers are commonplace in data analysis. Time series analysis is no exception. Noting that the effect of outliers on model identification statistics could be serious, this article is concerned with the problem of time series model specification in the presence of outliers. An iterative procedure is proposed to identify the outliers, to remove their effects, and to specify a tentative model for the underlying process. The procedure is essentially based on the iterative…

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The Prediction Approach to Robust Variance Estimation in Two-Stage Cluster Sampling

两阶段整群抽样中稳健方差估计的预测方法

Robust statistics are derived for estimating the error variance when a finite population total or a ratio of totals is estimated from a two-stage cluster sample in which the first-stage sampling fraction is small. The analysis is based on prediction (superpopulation) models that allow for very general correlation structure within clusters. Results are obtained for when all cluster sizes are known and for when sizes are known only for sample clusters. Ratio, regression, and…

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The Retransformed Mean after a Fitted Power Transformation

拟合幂变换后的原尺度均值估计

An approximate method is given to estimate the mean of a dependent variable after a linear model is fitted to the Box—Cox power transformation of this variable. The estimate is accurate except when the transformation power parameter is near zero. The properties of the estimate in the one-sample and regression cases are considered, by both asymptotic calculations and Monte Carlo simulations, and comparisons are made with the smearing estimate (Duan 1983). It is shown that…

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Alternative Methods for CPS Income Imputation

CPS 收入缺失值插补的替代方法

The U.S. Bureau of the Census imputes missing income items in the income supplement of the Current Population Survey (CPS) by a technique commonly known as the CPS hot deck. This article compares CPS hot deck imputations of wages and salary amounts with alternatives based on regression models for the logarithm of wages and salary and for the wage rate. Comparisons are effected by comparing imputations with an Internal Revenue Service (IRS) wages and salary amount found by an…

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An Introduction to Probability Theory.

概率论导论

This classic text and reference introduces probability theory for both advanced undergraduate students of statistics and scientists in related fields, drawing on real applications in the physical and biological sciences. The book makes probability exciting. -Journal of the American Statistical Association

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Mean Integrated Squared Error Sampling

基于平均积分平方误差的抽样

Stratified sampling is considered, where (a) the mean integrated squared error (MISE) metric is used in place of the mean squared error (MSE) metric; (b) the entire distribution [i.e., f(x)], rather than a property of the distribution [e.g., E(x)], is used as a target of the procedure; (c) the distribution f(x) is estimated by a truncated series (to counterbalance model complexity with sample size availability); and finally, (d) samples are taken both with and without…

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The Selection of Terms in an Orthogonal Series Density Estimator

正交级数密度估计中的项选择

We show that Kronmal and Tarter's well-known rule for selecting the terms in an orthogonal series density estimator can lead to poor performance and even inconsistency in certain cases. These difficulties arise when the underlying density has a nonmonotone sequence of Fourier coefficients, as is likely to be the case with sharply peaked or multimodal distributions. We suggest a way of overcoming these shortcomings.

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Combining Information on Measurement Error in the Errors-in-Variables Model

变量测量误差模型中测量误差信息的结合

For the regression model in which an explanatory variable contains measurement error, the instrumental variable and the correction for attenuation estimators of slope are considered. Although each requires extra information that is rarely available in ideal form, examinations of asymptotic variances and simulation results suggest that the correction for attenuation performs as well as a fairly strong instrumental variable when the measurement errors are not too large, and…

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