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医学筛查检验的贝叶斯推断：艾滋病分析中的实用近似AI 解读

SUMMARY In this paper, we develop large sample Bayesian methods for assessing the accuracy of screening tests that are used to detect antibodies to the human immunodeficiency virus in donated blood, and for assessing the prevalence of the disease in the population sampled from. We obtain approximate joint and marginal posterior distributions for the predictive values positive and negative of a test and, additionally, we obtain approximate predictive distributions for the…

线性参数模型中扩展最大似然估计的计算AI 解读

SUMMARY Methods are given for computing extended maximum likelihood estimates in which one or more parameter estimates are infinite at the supremum of the likelihood. The results are given for a broad class of regression-like models based on independent observations with linearly related parameters including, in particular, the generalized linear models. The estimation consists of two steps: A linear programming step to identify the infinite components and a more…

一般线性模型的误差诊断：重复测量与田间试验AI 解读

SUMMARY The large sample distribution of the recursive residual maximum likelihood residuals from the general linear model with dependent errors is derived. Further results are obtained from this distribution to aid the identification of an appropriate error model in the general linear model.

多项回归模型拟合优度检验的近似 Bartlett 调整AI 解读

SUMMARY For up to four categories and given sufficient replications per design point (eight or more seem to be enough), an adjusted likelihood ratio statistic for testing the goodness of fit of multinomial regression models is proposed. This adjustment does not depend on the multinomial model used and therefore will have a wide range of applications. It is certainly useful for the proportional odds model, introduced by McCullagh. This proportional odds model is used in some…

加权 Kaplan–Meier 统计量的大样本性质与最优性AI 解读

SUMMARY We propose a cumulative weighted difference in the Kaplan-Meier estimates as a test statistic for equality of distributions in the two-sample censored data survival analysis problem. For stability of such a statistic, the absolute value of the possibly random weight function must be bounded above by a multiple of (C −)1/2 + δ where 1 – C − is the left continuous censoring distribution function and δ > 0. For these weighted Kaplan–Meier (WKM) statistics, asymptotic…

形状统计分析中的 Procrustes 方法AI 解读

SUMMARY Two geometrical figures, X and Y, in RK, each consisting of N landmark points, have the same shape if they differ by at most a rotation, a translation and isotropic scaling. This paper presents a model-based Procrustes approach to analysing sets of shapes. With few exceptions, the metric geometry of shape spaces is quite complicated. We develop a basic understanding through the familiar QR and singular value decompositions of multivariate analysis. The strategy…

时间序列的留 K 个观测诊断AI 解读

Andrew G. Bruce, R. Douglas Martin; Leave-K-Out Diagnostics for Time Series, Journal of the Royal Statistical Society Series B: Statistical Methodology, Vo

概率密度导数估计的带宽选择AI 解读

SUMMARY An adaptation of least squares cross-validation is proposed for bandwidth choice in the kernel estimation of the derivatives of a probability density. The practicality of the method is demonstrated by an example and a simulation study. Theoretical justification is provided by an asymptotic optimality result.

利用增强谐波进行频率分析的新方法AI 解读

SUMMARY For stationary time series having a mixed spectrum, we introduce a new method for estimating the discrete frequencies based on amplification of the sine waves in the time series and on minimization of least squares regressions on amplified waves. Under the assumption that the continuous part of the spectrum arises from a stationary autoregressive moving average process, we show that the estimators for the discrete frequencies obtained with this method are strongly…

Bootstrap模拟的平衡设计AI 解读

SUMMARY Davison et al. (1986) have shown that finite bootstrap simulations can be improved by forcing balance in the aggregate of simulated data sets. Their methods yield first-order balance, which principally affects bootstrap estimation of bias. Here we extend the methodology to second-order balance, which principally affects bootstrap estimation of variance. The particular techniques involve Latin square and balanced incomplete block designs. Numerical examples are given…

多元自回归移动平均时间序列理论自协方差矩阵的计算AI 解读

SUMMARY Matrix expressions relating the theoretical autocovariances of autoregressive moving average (ARMA) processes to their parameters are derived and used to design an efficient procedure for computing autocovariance sequences of multivariate ARMA processes. The method proposed is more efficient than others suggested in the literature and, in particular, reduces the computational burden associated with exact maximum likelihood estimation of ARMA models. The closed form…

分离假设族的最优条件检验AI 解读

SUMMARY We consider, from the viewpoint of hypotheses testing, the problem of assigning the probability density function of a random variable X to one of two separate families of distributions. Our aim is to study the possibility of constructing best similar tests. For this, we characterize sufficient statistics for the union of the two families; completeness is also studied. We state conditions under which the test statistics are easily obtainable when both families are of…

实质研究假设、条件独立图与图链模型AI 解读

SUMMARY Graphs consisting of points, and lines or arrows as connections between selected pairs of points, are used to formulate hypotheses about relations between variables. Points stand for variables, connections represent associations. When a missing connection is interpreted as a conditional independence, the graph characterizes a conditional independence structure as well. Statistical models, called graphical chain models, correspond to special types of graphs which are…

抽样计数过程强度的非参数估计AI 解读

SUMMARY Sampled counting processes are often studied using methods for the analysis of stationary time series. We express some time series parameters as smoothed versions of corresponding point process parameters and use these relations to suggest estimates of the point process parameters. In addition, we propose a reconstructive approach to the estimation problem. We derive some properties of the estimators and apply them to data from meteorology, entomology and particle…

L-矩：利用次序统计量的线性组合分析与估计分布AI 解读

SUMMARY L-moments are expectations of certain linear combinations of order statistics. They can be defined for any random variable whose mean exists and form the basis of a general theory which covers the summarization and description of theoretical probability distributions, the summarization and description of observed data samples, estimation of parameters and quantiles of probability distributions, and hypothesis tests for probability distributions. The theory involves…

非均匀人口中的空间聚集检测AI 解读

SUMMARY A new method for detecting spatial clustering of events in populations with non-uniform density is proposed. The method is based on selecting controls from the population at risk and computing interpoint distances for the combined sample. Nonparametric tests are developed which are based on the number of cases among the k nearest neighbours of each case and the number of cases nearer than the k nearest control. The performance of these tests is evaluated analytically…

平滑 Bootstrap 的替代方法AI 解读

SUMMARY Bootstrap estimation of simple population functionals is considered. The smoothed bootstrap (Efron, 1979, 1982) is compared with an alternative estimation procedure based on resampling ideas of Kendall and Kendall (1980). Specific examples of the estimation problem are considered, showing that the competing estimators may display different qualitative behaviours.

门限自回归的似然比检验AI 解读

SUMMARY This paper addresses the null distribution of the likelihood ratio statistic for threshold autoregression with normally distributed noise. The problem is non-standard because the threshold parameter is a nuisance parameter which is absent under the null hypothesis. We reduce the problem to the first-passage probability associated with a Gaussian process which, in some special cases, turns out to be a Brownian bridge. It is also shown that, in some specific cases, the…

时间序列模型的分解聚合AI 解读

SUMMARY We develop a model disaggregation method to derive a disaggregate model from a given aggregate model, which is then used to perform data disaggregation. Since a time series model and its autocovariance structure are closely related, we approach the problem by exploring the possibility of estimating the autocovariance structure for the unobserved disaggregated series from the available autocovariances of an aggregate model. Let the time series aggregates be the…

EM 算法在惩罚似然估计中的应用AI 解读

SUMMARY The EM algorithm is a popular approach to maximum likelihood estimation but has not been much used for penalized likelihood or maximum a posteriori estimation. This paper discusses properties of the EM algorithm in such contexts, concentrating on rates of convergence, and presents an alternative that is usually more practical and converges at least as quickly.

摘要暂缺

Marshall–Olkin 指数分布的贝叶斯估计AI 解读

SUMMARY Bayes estimators of the parameters of the Marshall–Olkin exponential distribution are obtained when random samples from series and parallel systems are available. The estimators are with respect to the quadratic loss function, and the prior distribution allows for prior dependence among the components of the parameter vector. Exact and approximate highest posterior density credible ellipsoids for the parameters are also obtained. In contrast with series sampling, the…

广义线性测量误差模型中的得分检验AI 解读

SUMMARY Hypothesis tests in generalized linear models are studied under the condition that a surrogate w is observed in place of the true predictor x. The efficient score test for the hypothesis of no association depends on the conditional expectation E(x|w) which is generally unknown. The usual test substitutes w for E(x|w) and is asymptotically valid but not efficient. We investigate two new test statistics appropriate when w = x + z where z is an independent measurement…

SUMMARY We propose a simple adjustment for profile likelihoods. The aim of the adjustment is to alleviate some of the problems inherent in the use of profile likelihoods, such as bias, inconsistency and overoptimistic variance estimates. The adjustment is applied to the profile log-likelihood score function at each parameter value so that its mean is zero and its variance is the negative expected derivative matrix of the adjusted score function. For cases in which explicit…