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Estimation of the Distribution Function of a Continuous Type Random Variable through Randomized Response

通过随机化回答估计连续型随机变量的分布函数

In 1965 Stanley Warner [8] illustrated a technique whereby one could estimate from a sample the proportion of persons in a population possessing some characteristic X, without pointedly asking the question, “Do you possess characteristic X?”. The present article uses a variation of these ideas suggested by Warner in a later paper [7] to estimate the distribution function of a continuous-type random variable. The technique is illustrated by estimating an income distribution…

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Errors in Variables: A Consistent Estimator with Smaller MSE in Finite Samples

变量测量误差:有限样本均方误差更小的一致估计量

This article develops and examines the small sample properties of alternative estimators when the data is suspected to contain measurement error. Two types of estimators are considered: (1) a linear combination of the OLS and instrumental variable (IV) estimators and (2) a method of choosing between the OLS and IV estimators on the basis of sample information. Large sample approximations are used to derive optimal procedures that are then evaluated by Monte Carlo experiments…

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Some Results on the Estimation of Variance Components by MINQUE

利用 MINQUE 估计方差分量的若干结果

A specific solution is derived to an optimization problem posed in the general theory of C.R. Rao for the estimation of variance components. A class of MINQUE estimators of variance components is derived by considering the residuals from a weighted least squares analysis.

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Linear Discriminant Functions for Stationary Time Series

平稳时间序列的线性判别函数

Certain spectral approximations are applied to the problem of discriminating between two normal processes by linear filtering. Limiting values for the (1) Kullback-Leibler discrimination information rate, (2) J-divergence rate and (3) detection probability are expressed in terms of the spectral densities of the two populations and the Fourier-Stieltjes transform of the mean difference between them. Spectral approximations to (1), (2) and (3), convenient for computing, are…

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Bivariate Probit Analysis: Minimum Chi-Square Methods

双变量 Probit 分析:最小卡方方法

In this article we propose two minimum chi-square estimators for a bivariate probit model. We call one estimator the Full Information and the other Limited Information Minimum Chi-Square because the first takes account of all the a priori information while the second does not. Both estimators are shown to be consistent. Moreover, the first is shown to be asymptotically as efficient as the maximum likelihood estimator and yet is computationally much simpler. For illustration,…

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An Errors-In-Variables Analysis of Managerial Role Performance

管理者角色表现的变量测量误差分析

A linear model with measurement error in the independent variables is considered. An errors-in-variables procedure is presented that provides estimators of the coefficients and their variances. If the dependent variable has multiple measures, the total variance of the dependent variable can be decomposed into measurement error, variance of true values explained by the true values of the independent variables and variance of true values not explained by the model. An…

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A Regression Method for Estimating Population Changes of Local Areas

估计地方人口变化的回归方法

A regression method is presented in which current sample data and symptomatic information are combined to estimate postcensal populations for local areas. This procedure was tested for counties and states using 1970 Census data, and the resulting estimates were found to be more accurate than estimates computed by standard demographic procedures for the same period. The ratio-correlation estimates were the most accurate series of standard estimates. When this series was added…

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Forecasting Accuracy of the McGraw-Hill Anticipatory Data

McGraw-Hill 预期调查数据的预测准确性

This study analyzes the forecast accuracy of the McGraw-Hill (M-H) anticipations with one- to four-year horizons of investment, sales and capacity for major manufacturing industries for the period 1948–71. Average absolute percentage errors are presented for each anticipation series. In comparison to the BEA survey of one-year investment anticipations, the M-H data are generally less accurate. On the other hand, in forecasting experiments the M-H series are shown to be more…

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An Algorithm for Determining the Asymptotically Best Linear Estimate of the Mean from Multiply Censored Logistic Data

多重删失 Logistic 数据下均值渐近最优线性估计的算法

An algorithm is considered for allocating an optimum spacing for the asymptotically best linear estimate (ABLE) of the mean μ, when the standard deviation πσ 0/√3 of the logistic distribution is known, based on k order statistics selected from a large multiply censored sample. This algorithm can be applied to problems of estimating the location parameter of the normal, Cauchy and extreme-value distribution when the scale parameter is known and estimating the scale parameter…

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Iterative Instrumental Variables Method and Estimation of a Large Simultaneous System

迭代工具变量法与大型联立方程系统的估计

The estimation method proposed here offers a way to achieve consistent estimates of simultaneous systems for which the number of observations falls short of the number of predetermined variables in the system as a whole. This method, called the iterative instrumental variables (IIV) method, can be described as iterative use of the instrumental variable interpretation of the 2SLS as given by Klein. A discussion is presented on convergence of the iterative procedure and the…

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Estimation of Reliability in a Multicomponent Stress-Strength Model

多部件应力—强度模型中的可靠性估计

A stress-strength model is formulated for s of k systems consisting of identical components. We consider minimum variance unbiased estimation of system reliability for data consisting of a random sample from the stress distribution and one from the strength distribution when the two distributions are exponential with unknown scale parameters. The asymptotic distribution is obtained by expanding the unbiased estimate about the maximum likelihood value and establishing their…

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Sensitivity Analysis of the Fixed Point Vector of Transition Matrices

转移矩阵不动点向量的敏感性分析

The fixed point vector of a regular or ergodic transition matrix is given for a transition matrix, P, when an entire row is changed. The computation of the fixed point vector involves only vector-matrix multiplication and addition, and is based on the initial computation of the pseudo-inverse of (P – I). Sensitivity analysis of the Markov Chain is easily performed utilizing this result.

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Bias of Two Classification Procedures in a Dichotomous Population

二分类总体中两种分类程序的偏差

Two classification procedures are considered in estimating a proportion P in a dichotomous population. Given that classifiers may be subject to error, sufficient conditions are obtained on the probabilities of misclassification of the classifiers such that the bias of one procedure will always be smaller than the bias of the other procedure for typical values of P found in practice. The mean squared error of the former procedure is also shown to be superior for moderate…

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Partition Regression

分区回归

This article considers an approach to partition or unconstrained piece-wise regression which begins with an ordering of the observations and applies a dynamic program from cluster analysis to greatly reduce the number of calculations involved in its application.

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A Simple Test for Serial Correlation in Regression Analysis

回归分析中序列相关的简单检验

An exact test for serial correlation in regression models is proposed based on the fact that under classical assumptions and including normality for disturbances, the successive quantities are independent N(0, σ2). For various types of data the power of the proposed test compares favorably with that of the BLUS test, but neither test is as powerful as the full Durbin-Watson procedure in which an approximate significance point is calculated when the bounds test is…

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Distribution of Residual Autocorrelations in Multiple Autoregressive Schemes

多变量自回归模型中残差自相关的分布

Box and Pierce [3] showed that the residual autocorrelations computed from an autoregressive-moving average time series model (single variate) can be successfully utilized for testing the goodness of fit. Here we extend their results to multiple autoregressive time series models. It is shown that the residual autocorrelations can be approximately represented as a singular linear transform of the corresponding white noise autocorrelations and that they possess a multivariate…

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Adaptive Robust Procedures: A Partial Review and Some Suggestions for Future Applications and Theory

自适应稳健程序:部分综述及应用与理论建议

After providing some background for the need to consider estimates other than those resulting from normal theory, there is a brief review of some nonadaptive robust estimators. We introduce adaptive estimators using those of Tukey and McLaughlin, Jaeckel, Johns, Birnbaum and Miké, Takeuchi, Hàjek, van Eeden, and Beran. Adaptive estimators based on preliminary testing and Stein-like procedures are then considered, and recommendations are made on how to select the amount of…

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Comparative Robustness of Six Tests in Multivariate Analysis of Variance

多元方差分析中六种检验的稳健性比较

Monte Carlo methods were used to study the performance of the largest-root test, two trace-type tests and three determinantal tests in the fixed-effects MANOVA model when certain assumptions are violated. Results indicated that for protection against nonnormality and heterogeneity of covariance matrices, the largest-root test should be avoided, while the Pillai-Bartlett trace test may be recommended as the most robust of the MANOVA tests, with adequate power to detect true…

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Empirical Bayes Methods Applied to Estimating Fire Alarm Probabilities

用于估计火警真实性概率的经验贝叶斯方法

An empirical Bayes approach is used to derive a Stein-type estimator of a multivariate normal mean when the components have unequal variances. This estimator is applied to estimating the probability that a fire alarm reported from a particular street box signals a structural fire rather than a false alarm or other emergency. The approach is to group alarm boxes into relatively homogeneous neighborhoods and to make empirical Bayes estimates of the “probability structural” for…

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Bias of Two Classification Procedures in a Dichotomous Population

二分类总体中两种分类程序的偏差

Two classification procedures are considered in estimating a proportion P in a dichotomous population. Given that classifiers may be subject to error, sufficient conditions are obtained on the probabilities of misclassification of the classifiers such that the bias of one procedure will always be smaller than the bias of the other procedure for typical values of P found in practice. The mean squared error of the former procedure is also shown to be superior for moderate…

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A Regression Method for Estimating Population Changes of Local Areas

估计地方人口变化的回归方法

A regression method is presented in which current sample data and symptomatic information are combined to estimate postcensal populations for local areas. This procedure was tested for counties and states using 1970 Census data, and the resulting estimates were found to be more accurate than estimates computed by standard demographic procedures for the same period. The ratio-correlation estimates were the most accurate series of standard estimates. When this series was added…

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Forecasting Accuracy of the McGraw-Hill Anticipatory Data

McGraw-Hill 预期调查数据的预测准确性

This study analyzes the forecast accuracy of the McGraw-Hill (M-H) anticipations with one- to four-year horizons of investment, sales and capacity for major manufacturing industries for the period 1948–71. Average absolute percentage errors are presented for each anticipation series. In comparison to the BEA survey of one-year investment anticipations, the M-H data are generally less accurate. On the other hand, in forecasting experiments the M-H series are shown to be more…

AI 解读阅读原文 ↗BibTeX ↓