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指数型随机过程中的有效序贯估计AI 解读

A class of random processes whose likelihood functions are of exponential type is considered. A necessary and sufficient condition for a stopping time to be efficient (in the Cramer-Rao sense) is proved. This result is obtained after proving a characterization theorem, which asserts that after a suitable random-time transformation such processes become processes with stationary independent increments, by applying the solution of the problem of efficient sequential estimation…

随机截断下乘积极限估计量的渐近性质AI 解读

Many authors have considered the problem of estimating a distribution function when the observed data is subject to random truncation. A prominent role is played by the product limit estimator, which is the analogue of the Kaplan-Meier estimator of a distribution function under random censoring. Wang and Jewell (1985) and Woodroofe (1985) independently proved consistency results for this product limit estimator and showed weak convergence to a Gaussian process. Both papers…

非紧参数空间下非线性回归的一致估计量AI 解读

Sufficient conditions are given in order to ensure the existence of a sequence of strongly consistent estimators of unknown parameters in a nonlinear regression model. The primary difference between this and earlier work is in the generality of the parameter space. Indeed, the parameter space is assumed to be any separable, completely regular topological space; in particular, this includes all separable metric spaces.

变点泊松过程的渐近推断AI 解读

Easily implemented asymptotic off-line procedures for the change-point Poisson process with $\lambda(t)$, the intensity at time $t$, equal to $\lambda_1$ if $t \leq \tau$ and to $\lambda_2$ if $t > \tau$, are developed. They may also be applied to a problem of estimation of the location of a discontinuity in density discussed by Chernoff and Rubin (1956). A test for change is noted, a test of the hypothesis that $\tau = \tau_0$ is proposed, and point and interval estimates…

非正态不平衡嵌套混合模型中方差分量 ANOVA 估计的渐近正态性AI 解读

Despite their lack of optimality in unbalanced normally distributed models, the ANOVA estimates of components of variance are convenient and widely used. The hierarchal (nested) design is well suited to this estimation scheme. In this paper the nonnormal, unbalanced hierarchal design is considered and mild conditions for a sequence of such designs are specified so that the vector of normalized ANOVA estimates converges to a multivariate normal distribution. The nested…

椭圆等高密度的概率不等式及其在序约束推断中的应用AI 解读

Anderson (1955) established the monotonicity of the integral of a symmetric, unimodal density over translates of a symmetric, convex set. A similar result is developed for integrals of elliptically contoured, unimodal densities over translates of an asymmetric, convex set in certain directions related to the set. This result is used to establish some monotonicity properties of the power functions of the likelihood ratio tests for determining whether or not a vector of normal…

单调潜变量模型中的条件关联与单维性AI 解读

Latent variable models represent the joint distribution of observable variables in terms of a simple structure involving unobserved or latent variables, usually assuming the conditional independence of the observable variables given the latent variables. These models play an important role in educational measurement and psychometrics, in sociology and in population genetics, and are implicit in some work on systems reliability. We study a broad class of latent variable…

渐近独立的尺度无关间距及其异常值检验应用AI 解读

Motivated by the construction of independent scale-free spacings for the exponential distribution, analogous quantities are defined for an arbitrary distribution, and their joint asymptotic behaviour studied under suitable tail conditions. These scale-free spacings provide a unified approach to the problem of consecutive discordancy testing when location and scale parameters are unknown. A normal example is discussed and the accuracy of the approximations assessed via some…

An Edgeworth expansion with remainder $o(N^{-1})$ is established for a $U$-statistic with a kernel $h$ of degree 2. The assumptions involved appear to be very mild; in particular, the common distribution of the summands $h(X_i, X_j)$ is not assumed to be smooth.

构造置信区间需要多少次 Bootstrap 模拟AI 解读

We make two points about the number, $B$ of bootstrap simulations needed to construct a percentile-$t$ confidence interval based on an $n$ sample from a continuous distribution: (i) The bootstrap's reduction of error of coverage probability, from $O(n^{-1/2})$ to $O(n^{-1})$, is available uniformly in $B$, provided nominal coverage probability is a multiple of $(B + 1)^{-1}$. In fact, this improvement is available even if the number of simulations is held fixed as $n$ increas…

Bootstrap 与置信区间AI 解读

We derive an explicit formula for the first term in an unconditional Edgeworth-type expansion of coverage probability for the nonparametric bootstrap technique applied to a very broad class of "Studentized" statistics. The class includes sample mean, $k$-sample mean, sample correlation coefficient, maximum likelihood estimators expressible as functions of vector means, etc. We suggest that the bootstrap is really an empiric one-term Edgeworth inversion, with the bootstrap…

不变量与似然比统计量AI 解读

Because the likelihood ratio statistic is invariant under reparameterization, it is possible to make a large-sample expansion of the statistic itself and of its expectation in terms of invariants. In particular, the Bartlett adjustment factor can be expressed in terms of invariant combinations of cumulants of the first two log-likelihood derivatives. Such expansions are given, first for a scalar parameter and then for vector parameters. Geometrical interpretation is given…

非线性回归中参数子集的曲率AI 解读

The relative curvature measures of nonlinearity proposed by Bates and Watts (1980) are extended to an arbitrary subset of the parameters in a normal, nonlinear regression model. In particular, the subset curvatures proposed indicate the validity of linearization-based approximate confidence intervals for single parameters. The derivation produces the original Bates-Watts measures directly from the likelihood function. When the intrinsic curvature is negligible, the…

指数性与平均剩余寿命趋势转折的检验AI 解读

Given that an item is of age $t$, the expected value of the random remaining life is called the mean residual life (MRL) at age $t$. We propose two new nonparametric classes of life distributions for modeling aging based on MRL. The first class of life distributions consists of those with "increasing initially, then decreasing mean residual life" (IDMRL). The IDMRL class models aging that is initially beneficial, then adverse. The second class, "decreasing, then increasing…

更新函数的非参数估计AI 解读

The renewal function is a basic tool used in many probabilistic models and sequential analysis. Based on a random sample of size $n$, a nonparametric estimator of the renewal function is introduced. Asymptotic properties of the estimator such as consistency and asymptotic normality are developed. A discussion of an application to warranty analysis is also provided.

删失条件下二元生存函数的非参数估计AI 解读

A new family of estimators of a bivariate survival function based on censored vectors is obtained from a decomposition of the bivariate survival function. These estimators are uniformly consistent under bivariate censoring and are self-consistent under univariate censoring.

Shapiro–Wilk 正态性检验 W 统计量的渐近分布AI 解读

Twenty years have elapsed since the Shapiro-Wilk statistic $W$ for testing the normality of a sample first appeared. In that time a number of statistics that are close relatives of $W$ have been found to have a common (known) asymptotic distribution. It was assumed, therefore, that $W$ must have that asymptotic distribution. We show this to be the case and examine the norming constants that are used with all the statistics. In addition the consistency of the $W$ test is…

检测分布变化的最优停止时间AI 解读

It is shown that Page's stopping time is optimal for the detection of changes in distributions, in a well defined sense. This work is a generalization of an existing result where it was shown that Page's stopping time is optimal asymptotically.

回归分析中的 Jackknife、Bootstrap 与其他重抽样方法AI 解读

Motivated by a representation for the least squares estimator, we propose a class of weighted jackknife variance estimators for the least squares estimator by deleting any fixed number of observations at a time. They are unbiased for homoscedastic errors and a special case, the delete-one jackknife, is almost unbiased for heteroscedastic errors. The method is extended to cover nonlinear parameters, regression $M$-estimators, nonlinear regression and generalized linear…

Good 非参数覆盖率估计量的效率AI 解读

The asymptotic efficiency of Good's nonparametric coverage estimator is obtained relative to the best estimator derived under the assumption that all classes are equally likely. Even when that assumption is true, Good's estimator is quite efficient, with an asymptotic relative efficiency of greater than 85% in all cases, and greater than 95% if the expected coverage is less than one-half.

基于回归残差的稳健尺度估计量的 Bahadur 表示AI 解读

We investigate the asymptotic behaviour of the median deviation and the semi-interquartile range based on the residuals from a linear regression model by deriving weak asymptotic representations for the estimators. These representations may be used to obtain a variety of central limit theorems and yield conditions under which the median deviation and the semi-interquartile range are asymptotically equivalent. The results justify the use of the estimators as concommitant…

随机删失下经验测度的局部收敛及其在密度与风险率估计中的应用AI 解读

In this paper, we study the local deviations of the empirical measure defined by the Kaplan-Meier (1958) estimator for the survival function. The results are applied to derive best rates of convergence for kernel estimators for the density and hazard rate function in the random censorship model.

有限总体抽样的贝叶斯统计推断AI 解读

Bayesian statistical inference for sampling a finite population is studied by using the Dirichlet-multinomial process as prior. It is shown that if the finite population variables have a Dirichlet-multinomial prior, then the posterior distribution of the inobserved variables given a sample is also Dirichlet-multinomial. If the population size tends to infinity (the sample size is fixed), sampling without replacement from a Dirichlet multinomial process is equivalent to the…

线性过程误差回归中 GLSE 与 MLE 的二阶风险结构AI 解读

In a regression model with an error that is a general linear process, the second-order expansion of the risk matrix of GLSE or MLE is obtained. a set of sufficient conditions for the effect of estimating the structural parameter of the linear process to vanish in the above expasion is obtained. The relation of the covariance matrix of SLSE with those of GLSE and MLE up to $O(T^-2)$ is elucidated.