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双系统估计中人口登记概率异质性的估计AI 解读

We show how conditional logistic regression can be used to estimate the probability of being enumerated in a census and apply the model to the 1990 Post-Enumeration Survey (PES) in the United States. The estimates can be used in the estimation of population size and the estimation of correlation bias, for example. Unlike the classical stratification approach, the logistic approach permits the use of continuous explanatory variables. Model choice can be based on the standard…

在人口普查后调查估计中利用人口分析信息AI 解读

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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二元响应数据中 Fieller 区间的准确性AI 解读

Finney proposed the use of a fiducial interval for the median response dose based on Fieller's theorem. An alternative is to use the asymptotic confidence interval. The simulations by Abdelbasit and Plackett suggest that the two intervals have similar coverage probabilities. We compare the two intervals theoretically and in an expanded simulation study. Our results show that Fieller intervals are generally superior. An attempt is made to characterize how and when the two…

后分层：建模者的视角AI 解读

Post-stratification is a common technique in survey analysis for incorporating population distributions of variables into survey estimates. The basic technique divides the sample into post-strata, and computes a post-stratification weight w ih = rP h /r h for each sample case in post-stratum h, where r h is the number of survey respondents in post-stratum h, P h is the population proportion from a census, and r is the respondent sample size. Survey estimates, such as…

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有追访时不可忽略无应答混合模型中的多重插补AI 解读

One approach to inference for means or linear regression parameters when the outcome is subject to nonignorable nonresponse is mixture modeling. Mixture models assume separate parameters for respondents and nonrespondents; implementation by multiple imputation consists of repeatedly filling in missing values for nonrespondents, estimating parameters using the filled-in data, and then adjusting for variability between imputations. We evaluated the performance of this scheme…

多事件时间数据的半参数贝叶斯分析AI 解读

Multiple event time data (e.g., carcinogenic growths in different times and locations, multiple attacks of cardiac arrest) arise in various medical studies. A Bayesian analysis of such data based on proportional intensity model of multiple event time data is presented in this paper. The Bayesian structure is somewhat analogous to that used by Kalbfleisch in a proportional hazard model. An unobserved random frailty component is used in the proportional intensity model to take…

自回归时间序列均值与方差变化的贝叶斯推断及预测AI 解读

This article is concerned with statistical inference and prediction of mean and variance changes in an autoregressive time series. We first extend the analysis of random mean-shift models to random variance-shift models. We then consider a method for predicting when a shift is about to occur. This involves appending to the autoregressive model a probit model for the probability that a shift occurs given a chosen set of explanatory variables. The basic computational tool we…

非线性加性 ARX 模型AI 解读

We consider in this article a class of nonlinear additive autoregressive models with exogenous variables for nonlinear time series analysis and propose two modeling procedures for building such models. The procedures proposed use two backfitting techniques (the ACE and BRUTO algorithms) to identify the nonlinear functions involved and use the methods of best subset regression and variable selection in regression analysis to determine the final model. Simulated and real…

不等间距空间数据的连续ARMA模型拟合AI 解读

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…

广义置信区间AI 解读

The definition of a confidence interval is generalized so that problems such as constructing exact confidence regions for the difference in two normal means can be tackled without the assumption of equal variances. Under certain conditions, the extended definition is shown to preserve a repeated sampling property that a practitioner expects from exact confidence intervals. The proposed procedure is also applied to the problem of constructing confidence intervals for the…

通过Gibbs采样进行变量选择AI 解读

A crucial problem in building a multiple regression model is the selection of predictors to include. The main thrust of this article is to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure entails embedding the regression setup in a hierarchical normal mixture model where latent variables are used to identify subset choices. In this framework the promising subsets of predictors can be identified as those…

简单线性回归变化点似然比检验的稳健性AI 解读

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…

密度导数估计中的平滑偏差AI 解读

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…

自适应位置估计中平滑参数的交叉验证选择AI 解读

Abstract 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…

利用非参数泛函估计探索回归结构AI 解读

Average derivative functionals of regression are proposed for nonparametric model selection and diagnostics. The functionals are of the integral type, which under certain conditions allows their estimation at the usual parametric rate of n –1/2. We analyze asymptotic properties of the estimators of these functionals, based on kernel regression. These estimators can then be used for assessing the validity of various restrictions imposed on the form of regression. In…

ATS方法：非高斯数据的非参数回归AI 解读

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…

重复失效时间与时变协变量的图形展示及边际回归分析AI 解读

Recurrent event time data are common in medical research; examples include infections in AIDS patients and seizures in epilepsy patients. In this context, as well as in the more usual context of a single failure time variable, time-dependent covariates are frequently of interest. We suggest some rate functions that might be displayed when analyzing recurrent failure time data or when the effect of a categorical time-dependent covariate is of interest. Estimators of these…

非对称分布均值检验的计算密集方法AI 解读

For one-sided tests about the mean of a skewed distribution, the t test is asymptotically robust for validity; however, it can be quite inaccurate and inefficient with small sample sizes. Results presented here confirm that a procedure due to Johnson should be preferred to the t test when the parent distribution is asymmetrical, because it reduces the probability of type I error in cases where the t test has an inflated type I error rate and it is more powerful in other…

多个异常值的识别AI 解读

One approach to identifying outliers is to assume that the outliers have a different distribution from the remaining observations. In this article we define outliers in terms of their position relative to the model for the good observations. The outlier identification problem is then the problem of identifying those observations that lie in a so-called outlier region. Methods based on robust statistics and outward testing are shown to have the highest possible breakdown…

大麻非刑事化对医院急诊涉药事件的影响：1975—1978年AI 解读

Between 1973 and 1978, 12 states with collectively over one-third of the total U.S. population enacted laws that decriminalized the possession of marijuana. This article uses standard metropolitan statistical area (SMSA) level data on hospital emergency room drug episodes collected by the Drug Abuse Warning Network to measure the effect of changes in drug penalties on substance abuse crises. The regression models demonstrate that marijuana decriminalization was accompanied…

L1 统计分析及相关方法AI 解读

Prologue. Thoughts on Real Data and Statistics (Y. Dodge). Some Statistical Tools for the Analysis of Complex Molecular Spectra (A.F. Ruckstuhl). Estimation, Testing and Property Characterization. The Gauss Markov Property for the Median (G.W. Basset, Jr.,). A Class of Estimators Based on Adaptative Convex Combinations of Two Estimation Procedures (Y. Dodge, J. Jureckova). Robustness of L1 Regression in the Light of Linear Programming (J. Dupacova). A Linear Model with a…

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