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Seasonal Adjustment as a Practical Problem.

作为实践问题的季节调整

Seasonal adjustment as a practical problem. Prolegomena to actual seasonal adjustment. Mechanical seasonal adjustment methods. ARIMA models and seasonal adjustment. Structural time series models and seasonal adjustment. The adding up problem and seasonally adjusted monetary analysis. Causal methods of seasonal adjustment. Concluding observations. Annex. References. Indexes.

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Estimation of Population Coverage in the 1990 United States Census Based on Demographic Analysis

基于人口分析估计1990年美国人口普查覆盖率

This article presents estimates of net coverage of the national population in the 1990 census, based on the method of demographic analysis. The general techniques of demographic analysis as an analytic tool for coverage measurement are discussed, including use of the demographic accounting equation, data components, and strengths and limitations of the method. Patterns of coverage displayed by the 1990 estimates are described, along with similarities or differences from…

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Sequential Analysis for Censored Regression Data

删失回归数据的序贯分析

Motivated by Buckley and James' modification of the least squares procedure for censored regression data, we derive a score process that incorporates the time evolution and handles staggered entry data in a natural way. By censored regression data we mean that the responses are subject to a possible right censorship. Such cases often arise from clinical trials and industrial life tests. The score process can be interpreted as a weighted comparison of (transformed) survival…

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Smoothing Bias in Density Derivative Estimation

密度导数估计中的平滑偏差

This article discusses a generic feature of density estimation by local smoothing, namely that estimated derivatives and location score vectors will display a systematic downward (attenuation) bias. We study the behavior of kernel estimators, indicating how the derivative bias arises and showing a simple result. We then consider the estimation of score vectors (negative log-density derivatives), which are motivated by the problem of estimating average derivatives and the…

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ATS Methods: Nonparametric Regression for Non-Gaussian Data

ATS 方法:非高斯数据的非参数回归

ATS methods provide an approach to fitting curves and surfaces to data using nonparametric regression when distributions are not necessarily Gaussian. First, a small amount of local averaging (the “A” in ATS) is carried out, then a variance-stabilizing transformation is applied (“T”), and finally the result is smoothed (“S”) using a nonparametric regression procedure. ATS methods are quite broad in terms of applications; in this article we show how they can be used for…

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Response and Sequencing Errors in Surveys: A Discrete Contagious Regression Analysis

调查中的回答与跳题顺序错误:离散传染回归分析

Skip sequencing in surveys reduces costs but also acts as a mechanism of contagion in transmitting error from one survey item to subsequent items. The error process is modeled as a contagious, stochastic one in which both the initiating and induced errors follow the Poisson distribution. The resulting compound distribution, first used by Thomas in 1949, is then used as the basis of a discrete contagious regression model in which characteristics of respondents, subject…

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Using Information From Demographic Analysis in Post-Enumeration Survey Estimation

在人口普查后调查估计中利用人口分析信息

Population estimates from the 1990 Post-Enumeration Survey (PES), used to measure decennial census undercount, were obtained from dual system estimates (DSE's) that assumed independence within strata defined by age-race-sex-geography and other variables. We make this independence assumption for females, but develop methods to avoid the independence assumption for males within strata by using national level sex ratios from demographic analysis (DA). This is done by using DSE…

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Fitting Continuous ARMA Models to Unequally Spaced Spatial Data

不等间距空间数据的连续 ARMA 模型拟合

Methods for fitting continuous spatial autoregressive moving average (ARMA) models to unequally spaced observations in two dimensions are reviewed and extended. These are models with rational two-dimensional spectra. Assuming Gaussian input noise and observational errors, maximum likelihood methods are used to estimate the ARMA parameters and the regression coefficients of the deterministic trend. When the number of observations is too large for exact maximum likelihood…

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Robustness of the Likelihood Ratio Test for a Change in Simple Linear Regression

简单线性回归变化点似然比检验的稳健性

This article examines the robustness of the likelihood ratio tests for a change point in simple linear regression. We first summarize the normal theory of Kim and Siegmund, who have considered the likelihood ratio tests for no change in the regression coefficients versus the alternatives with a change in the intercept alone and with a change in the intercept and slope. We then discuss the robustness of these tests. Using the convergence theory of stochastic processes, we…

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A Cross-Validatory Choice of Smoothing Parameter in Adaptive Location Estimation

自适应位置估计中平滑参数的交叉验证选择

This article proposes a new data-driven method for selecting the smoothing parameter involved in constructing kernel-based adaptive location estimators. The method consists of minimizing a cross-validatory criterion with respect to the bandwidth occurring in the kernel-type estimators of the efficient score function. It is shown that the location estimator with a data-driven bandwidth selector is indeed an adaptive estimator. A simulation study reveals that the method is…

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Combining Independent Tests in Linear Models

线性模型中独立检验的合并

A class of independent linear models is considered, where the variances of the different models are unequal but they have a common vector parameter θ occurring in their mean vectors. For testing the hypothesis H 0: θ = 0, some exact test procedures are derived that combine the information from all the models. The procedures are extensions of the test suggested by Cohen and Sackrowitz for recovering interblock information in balanced incomplete block designs. Simulation…

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Nonparametric Estimation of Rate Equations for Nutrient Uptake

营养吸收速率方程的非参数估计

Knowledge of the rate of a biological process is important for characterizing the system and is necessary for gaining a deeper understanding of the process. Consider measurements, Y, made over time on a system following the model Y = f(t) + e, where f is a smooth, unknown function and e is measurement error. Although most statistical methodology has focused on estimating f(t) or f′(t), in some applications what is of real biological interest is the relationship between f and…

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Maximum Likelihood Estimation of Regression Models with Stochastic Trend Components

含随机趋势成分的回归模型极大似然估计

This article is concerned with the estimation of a regression model with a stochastic trend component. It is shown that the probability of estimating the trend to be deterministic is very sensitive to the type of likelihood function used as the basis of inference.

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Linear Regression Analysis for Highly Stratified Failure Time Data

高度分层失效时间数据的线性回归分析

In this article we consider cases where data consist of many small and independent groups of correlated failure time observations. For each failure time, which may be censored, some important covariates are also recorded. Our goal is to examine the covariate effects on the individual failure time observations. We assume that the logarithm of each failure time is linearly related to its covariates. We then take a population-averaged model approach to obtain inference…

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Adaptive Smoothing and Density-Based Tests of Multivariate Normality

自适应平滑与基于密度的多元正态性检验

Methods of adaptive smoothing of density estimates, where the amount of smoothing applied varies according to local features of the underlying density, are investigated. The difficulties of applying Taylor series arguments in this context are explored. Simple properties of the estimates are investigated by numerical integration and compared with the fixed kernel approach. Optimal smoothing strategies, based on the multivariate Normal distribution, are derived. As an…

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Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation

二元核密度估计中平滑参数化的比较

The basic kernel density estimator in one dimension has a single smoothing parameter, usually referred to as the bandwidth. For higher dimensions, however, there are several options for smoothing parameterization of the kernel estimator. For the bivariate case, there can be between one and three independent smoothing parameters in the estimator, which leads to a flexibility versus complexity trade-off when using this estimator in practice. In this article the performances of…

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Multivariate Normal Mixtures: A Fast Consistent Method of Moments

多元正态混合:快速且一致的矩估计方法

A longstanding difficulty in multivariate statistics is identifying and evaluating nonnormal data structures in high dimensions with high statistical efficiency and low search effort. Here the possibilities of using sample moments to identify mixtures of multivariate normals are investigated. A particular system of moment equations is devised and then shown to be one that identifies the true mixing distribution, with some limitations (indicated in the text), and thus…

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Predicting Shifts in the Mean of a Multivariate Time Series Process: An Application in Predicting Business Failures

多元时间序列均值变化预测:企业失败预测应用

A firm in the early stages of financial distress exhibits characteristics different from those of healthy firms. As the economic condition of a firm worsens, its financial characteristics shift toward those of failed firms. Practitioners in the financial sector have long been interested in the early detection of a firm's slide toward insolvency. Several models have been developed with this purpose in mind, but these older models are static in nature. Therefore, a need exists…

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Experimental Design for Clonogenic Assays in Chemotherapy

化疗克隆形成测定的实验设计

One approach to estimating the number of cells with high growth potential in a cancer patient is the assessment of tumor cell colony formation in semisolid medium. A potential indicator of the clinical response to a specific drug is the capacity of the drug to reduce the formation of cell colonies. Often, a Poisson log-linear model provides an adequate representation of the dose-response curve. This model is then summarized by the dose required to reduce the number of…

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Bayes and Empirical Bayes Procedures for Comparing Parameters

参数比较的贝叶斯与经验贝叶斯方法

The number of successes out of the total number of trials is observed for each of a set of N independent binomial experiment's and the associated success probabilities are compared. Ranking procedures for comparing these success probabilities are constructed under circumstances where the number of trials for each of the experiments may differ by a large amount. A loss function is constructed that represents an appropriate measure of distance between a given ranking of the…

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Bayesian Analysis of Binary and Polychotomous Response Data

二元与多类别响应数据的贝叶斯分析

A vast literature in statistics, biometrics, and econometrics is concerned with the analysis of binary and polychotomous response data. The classical approach fits a categorical response regression model using maximum likelihood, and inferences about the model are based on the associated asymptotic theory. The accuracy of classical confidence statements is questionable for small sample sizes. In this article, exact Bayesian methods for modeling categorical response data are…

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