论文检索

混合比例的最小距离非参数估计AI 解读

SUMMARY Hall (1981a) develops a method of estimating mixture proportions using empirical distribution functions and a distance measure. A similar approach is suggested here based on density estimates. The method is applicable to general discrete data and multivariate data as well as to univariate continuous data and to ordered categorical data. For convenient quadratic distance measures the asymptotic theory is developed and remarks are made about practical implementation.…

交叉验证平滑样条的贝叶斯“置信区间”AI 解读

SUMMARY We consider the model Y(ti)=g(ti) + ∈i, i = 1, 2, …, n, where g(t), t ∈ [0, 1] is a smooth function and the {∈i} are independent N(0, σ2) errors with σ2 unknown. The cross-validated smoothing spline can be used to estimate g non-parametrically from observations on Y(ti), i= 1, 2, …, n, and the purpose of this paper is to study confidence intervals for this estimate. Properties of smoothing splines as Bayes estimates are used to derive confidence intervals based on…

空间中位数的统计用途AI 解读

SUMMARY The spatial median, called the mediancentre in an earlier paper by J. C. Gower, is defined as the bivariate location measure to minimize the sum of absolute distances to observations. its asymptotic efficiency relative to the sample mean vector with normal data is shown to exceed the usual univariate 2/π = 0.637. its estimating equations have an angular aspect and are used to develop “angle tests”, which are analogues of sign tests in one dimension.

关于删失与替代响应变量的一点讨论AI 解读

Summary Survival data are often subject to right censoring and to a consequent loss of information about the effect of explanatory variables. Sometimes it is possible to recover some of this lost information via a surrogate response variable measured on censored individuals and intended to predict the remaining life-time. This possibility is studied theoretically under idealized assumptions.

删失数据局部最强秩检验的统一推导方法AI 解读

Summary In this note a unified way of deriving locally most powerful rank tests for censored data is given. A lemma is proven. This lemma is then used to derive LMP rank tests.

论 Sprent 的广义最小二乘估计量AI 解读

Summary This paper studies the asymptotic properties of Sprent's (1966) generalized least-squares estimator of the slope parameter in a functional relationship model which allows errors at different data points be correlated. Consistency is established and the asymptotic variance derived. When the Joint distribution of the errors is normal, in which case Sprent's estimator coincides with the maximum likelihood estimator, the asymptotic variance formula is further simplified…

二分类预测中 Goodman–Kruskal λ 的精确检验AI 解读

Summary Goodman and Kruskal (1954) introduced a measure λ of predictive association when predicting the category of a variable B from a category of a variable A. The measure λ is such that 0 ≤ λ ≤ 1 with a zero value meaning no predictive gain while λ = 1 indicates a perfect predictive association between A and B. Thus, the test of H 0: λ = 0 versus H 1: λ > 0 is of prime importance, since it is entirely analogous to a test for significance of regression or correlation. We…

抽样理论中的一般完备性定理AI 解读

Summary Generalized symmetry of designs and estimators is defined to be invariance under a subgroup of the group of label permutations. A simple sufficient condition in terms of the design is given for the generalized order statistic, of which each generalized symmetric estimator is a function, to be complete. This condition is shown also to be necessary when the range of possible values for each characteristic is sufficiently large.

一种基于第 k 近邻的聚类程序AI 解读

Summary Due to the lack of development in the probabilistic and statistical aspects of clustering research, clustering procedures are often regarded as heuristics generating artificial clusters from a given set of sample data. In this paper, a clustering procedure that is useful for drawing statistical inference about the underlying population from a random sample is developed. It is based on the uniformly consistent kth nearest neighbour density estimate, and is applicable…

Summary The fit of a regression predictor to new data is nearly always worse than its fit to the original data. Anticipating this shrinkage leads to Stein-type predictors which, under certain assumptions, give a uniformly lower prediction mean squared error than least squares. Shrinkage can be particularly marked when stepwise fitting is used: the shrinkage is then closer to that expected of the full regression rather than of the subset regression actually fitted. Preshrunk…

广义线性模型的改进似然比统计量AI 解读

Summary This paper gives a general formula for the expected value of the likelihood ratio statistic for generalized linear models, corrected up to terms of order n -1, where n is the size of the sample. The application of this formula to some models is illustrated.

原点未知平移的连续单变量分布参数估计AI 解读

Summary A general method of estimating parameters in continuous univariate distributions is proposed. It is especially suited to cases where one of the parameters is an unknown shifted origin. This occurs, for example, in the three-parameter lognormal, gamma and Weibull models. For such distributions it is known that maximum likelihood (ML) estimation can break down because the likelihood is unbounded and this can lead to inconsistent estimators. Properties of the proposed…

摘要暂缺

摘要暂缺

利用符号秩对匹配对进行似然推断AI 解读

SUMMARY Exact and approximate inference based on the marginal likelihood which results from the signed ranks of the within pair differences of independent matched pairs is considered. Inference is made using Bayesian ideas. A quickly computed approximate analysis is introduced and this is shown to be extremely good when the within pair differences are assumed to have a normal distribution. Numerical comparisons are also made when the differences have a logistic distribution,…

不完整数据的核密度估计AI 解读

SUMMARY The problem of using non-parametric methods to estimate multivariate density functions from incomplete continuous data does not appear to have been considered before. Methods of producing kernel functions on incomplete observations are suggested involving averaging over the missing variables or substitution of them by simulated values. Consistency of the procedures in terms of integrated mean squared error is investigated and optimal choice of smoothing parameter is…

非线性自回归型时间序列模型的递归估计AI 解读

SUMMARY An adaptive estimation principle is considered for non-standard time series models; non-linear autoregressive processes in one dimension. Because of the recursive nature of the resulting estimator, it is computationally appealing, especially when a time series is considered as a flow of data. The least squares estimator is, for example, quite likely to be inferior. Asymptotic properties are derived under fairly weak assumptions, and special applications are…

减少采样操作次数的序贯估计AI 解读

SUMMARY A method is proposed for accelerating the sequential estimation procedure due to Anscombe, Chow and Robbins. It enables the number of sampling operations to be reduced by any predetermined factor, at the expense of only a slight increase in the expected sample size. The large sample theory is outlined, and some numerical computations provided to demonstrate the practicality of the procedure for smaller samples.

二元结局观察研究对未观测二元协变量的敏感性评估AI 解读

SUMMARY This paper proposes a simple technique for assessing the range of plausible causal conclusions from observational studies with a binary outcome and an observed categorical covariate. The technique assesses the sensitivity of conclusions to assumptions about an unobserved binary covariate relevant to both treatment assignment and response. A medical study of coronary artery disease is used to illustrate the technique.

田间试验的最近邻分析AI 解读

SUMMARY The paper is in two parts. Part I presents results of a Monte Carlo randomization study of Papadakis's covariance method of NN analysis which show that (i) a non-iterated Papadakis analysis tends to be conservatively biassed; (ii) iteration of the analysis as suggested by Bartlett (1978) leads to substantial positive bias in the treatment F ratio; (iii) the method is very inefficient when there are substantial trend effects in the data. A theoretical explanation of…

混合双随机泊松与自激点过程的线性强度模型AI 解读

Summary A flexible family of parametric models for intensity processes is introduced to represent a causal relationship between a point process and another stochastic process. Algorithms for the maximum likelihood computation and the procedure of model selection are discussed.

置换检验与置信区间的鞍点近似AI 解读

Summary Asymptotic approximations for the tail probabilities of certain statistics with complex moment generating functions are obtained by the usual methods of large deviation theory. It is pointed out that this approximation should be adequate over the entire range but of particular use for extreme tails. Approximations to the significance levels for one and two sample permutation tests are obtained and these tests are inverted to obtain approximate confidence intervals.…

双变量圆周数据的若干统计方法AI 解读

Summary A function of the smallest singular value of the cross product matrix between two circular unit vectors is suggested as a measure of correlation. It possesses most of the desirable properties for a correlation coefficient given by Jupp and Mardia (1980). The concept of cluster dependence is introduced. A good predictor of one unit vector given the other is shown to depend on the type of dependence observed. The wrapped bivariate normal is characterized.

斜率系数最大似然估计量的精确分布与近似分布AI 解读

Summary When the errors are normally independently distributed with equal variance, the maximum likelihood estimator of the slope of a linear functional relationship is the slope of the line minimizing the sum of squared deviations orthogonal to the line. The exact density and distribution of this estimator are obtained. Approximate distributions are obtained, and their accuracies are discussed.