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Dirichlet 先验下的秩次估计AI 解读

Suppose that a sample of size $n$ from a distribution function $F$ is obtained. However, only $r(< n)$ values from the sample are observed, say $X_1,\cdots, X_r$. Without loss of generality, we can consider $X_1,\cdots, X_r$ to be the first $r$ values in the (unordered) sample. The problem is to estimate the rank order $G$ of $X_1$ among $X_1,\cdots, X_n$. The situations of interest include $F$ nonrandom, either known or unknown, and $F$ random. The random case assumes that $F$…

给定均值与协方差的多元总体判别误差界AI 解读

Let $\mathscr{F}_1, \mathscr{F}_2$ be two families of $p$-variate distribution functions with specified means $\mathbf{\mu}_i (i = 1,2)$ and nonsingular covariance matrices $\Sigma_i$, and let $\pi_i$ be the prior probability assigned to $\mathscr{F}_i$ for $i = 1, 2$. The objective is to discriminate whether an observation $\mathbf{x}$ is from a distribution $F_1 \in \mathscr{F}_1$ or $F_2 \in \mathscr{F}_2$. Given a pair $F = (F_1, F_2)$ the error probability for…

回归分位数AI 解读

A simple minimization problem yielding the ordinary sample quantiles in the location model is shown to generalize naturally to the linear model generating a new class of statistics we term “regression quantiles.” The estimator which minimizes the sum of absolute residuals is an important special case. Some equivariance properties and the joint asymptotic distribution of regression quantiles are established. These results permit a natural generalization to the linear model of…

谱估计量精确有限样本分布的近似AI 解读

In this paper an explicit and computationally convenient expansion of the exact finite sample distribution function of a quasi-maximum likelihood spectral estimator is given. In the majority of practical situations it will be necessary to estimate certain nuisance parameters of the distribution. Therefore, a method of evaluating these parameters is suggested and some Monte-Carlo evidence concerning the practical implementation of the results is given. 1 INTRODUCTfON AN…

随机区组设计中实验误差正态性的大样本 KS 检验AI 解读

The weak convergence of the sample distribution function based on the estimated residuals in a randomized block design is considered under the null hypothesis of normality of the experimental errors. This result serves as a basis for deriving the limiting distribution of the Kolmogorov-Smirnov statistic computed from the estimated residuals. Quantiles of Monte Carlo simulations of the limiting distributions for various numbers of treatments are given. These results are…

一般线性模型中百分位数线的同时置信带AI 解读

This article is a generalization of the procedures developed by Steinhorst and Bowden (1971) for constructing confidence bands for the 100βth percentiles in the general linear model. Since the original procedure built these bands about a biased estimator of the 100βth precentile line, some other estimators were tried. While some improvement was noted, the results are not conclusive, suggesting that the best procedure has not been found yet.

极值分布的拟合优度检验AI 解读

In this paper we present goodness of fit tests for the extreme value distribution, based on the empirical distribution function statistics W2, U2and A2. Asymptotic percentage points are given for each of the three statistics, for the three cases where one or both of the parameters of the distribution must be estimated from the data. Slight modifications of the calculated statistics are given to enable the points to be used with small samples.

二元分布的单调依赖函数AI 解读

A new characterization of monotonic dependence is given here proceeding in a natural way from the consideration of a type of dependence weaker than quadrant dependence. More precisely, each bivariate distribution of $(X, Y)$ is transformed onto a pair of functions $^\mu{X, Y}$ and $^\mu{Y, X}$ defined on the interval $0 < p < 1$ and taking values from [-1, 1], with $^\mu{X, Y}(p)$ being a suitably normalized expected value of $X$ under the condition that $Y$ exceeds its $p$th…

序贯程序的一致性保证：分布类上的均匀性AI 解读

An extension of a central limit theorem for a mean of a random number of observations is given. A natural application occurs in the area of fixed-width confidence intervals. We provide an example which shows that the standard procedure does not preserve the intended coverage probability uniformly over nontrivial sets of distribution functions. The major weak convergence result is used to provide conditions for and a simple proof of such uniformity. The results are also shown…

向量值二元失效率的非参数估计AI 解读

Let $\mathbf{X} = (X_1, X_2)'$ be a bivariate random vector distributed according to an absolutely continuous distribution function $F(\mathbf{x})$ which has first partial derivatives. Let $\bar{F}(\mathbf{x}) = P(X_1 > x_1, X_2 > x_2).$ The vector-valued bivariate failure rate is defined as $\mathbf{r}(\mathbf{x}) = (r_1(\mathbf{x}), r_2(\mathbf{x}))',$ where $r_i(\mathbf{x}) = -\partial \ln \bar{F}(\mathbf{x})/\partial x_i (i = 1, 2)$. In this paper, we propose a smooth…

与经验分布函数线性界有关的分布AI 解读

$X_1, \cdots, X_n$ are i.i.d. Uniform (0, 1) rv's with empirical df $\Gamma_n$ and order statistics $0 < U_1 < \cdots < U_n < 1.$ Define random variables $U_\ast, i_\ast$ (for $n \geqq 2$) by $\max_{1\leqq i \leqq n - 1} \frac{U_{i + 1}}{i} = \frac{U_{i_\ast} + 1}{i_\ast}, U_\ast = U_{i_\ast + 1};$ $i_\ast + 1$ is the (random) index of the order statistic at which the maximum is achieved and $U_\ast$ is the value of that order statistic. The distributions of $(U_\ast, i_\ast)$…

二元分布的一族依赖性概念AI 解读

A family of concepts of stochastic dependence for bivariate distribution functions is introduced. Each concept gives rise to a family of bivariate distribution functions. We show the equivalence of some of these families with families of positively dependent distribution functions, which are known in the literature, and characterize some of them by notions from reliability theory. Interrelations among the various families are studied, and some moment inequalities are…

分数阶次序统计量及其应用AI 解读

Based upon Ferguson's Dirichlet process, we introduce an order-statistic process, a technical device which may be viewed as defining a continuum of fractional order statistics for any sample size. The order-statistic process provides an alternative to the quantile function essentially based on stochastic rather than linear interpolation. Its use in large-sample theory is suggested, and a simple proof is given that the order-statistic process, suitably normalized, converges…

样本量不超过 25 时 b1 的零分布及数值表AI 解读

For the sampling distribution of √b1 in samples of size n from a normal parent, leading singular terms of the density fn at its singularities are obtained by application of a general method given previously. These terms are combined with correcting terms, fitted by moments, to give approximations to fn, integrals of which were used to compute a table of the distribution function Fn for 4 ≤ n ≤ 12: for l3 ≤ n ≤ 25 Gram-Charlier expansions were used. A recurrence for the…

法庭科学中的一个统计问题AI 解读

SUMMARY The problem of deciding whether two sets of fragments have come from a common source frequently arises in forensic science. This paper provides a solution in the realistic case where the distribution is nonnormal. The normal case is also discussed because it is there easier to understand the nature of the solution and, in particular, its relationship to significance tests. The solution requires the distribution function of the product of standardized normal…

Summary In a review of tests based on spacings, Pyke (1965) constructs an empirical distribution function of uniform spacings, and suggests that goodness of fit problems could be investigated with Kolmogorov–Smirnov and Cramér–von Mises type statistics when applied to this empirical distribution function, were the appropriate exact or asymptotic critical values available. It is shown in this note that the limiting distributions of these statistics are indeed available, but…

基于 U 统计量的位置估计量AI 解读

Let $X_1, \cdots, X_n$ be i.i.d. $F$, and estimate the median of $F$ by the median $T_\beta$ of $\beta X_i + (1 - \beta)X_j, i \neq j$, where $\beta$ is a fixed positive constant. Then $T_\beta$ is the solution of a $U$-statistic equation from which its asymptotic normality is readily derived. The asymptotic relative efficiency of $T_\beta$ is computed for a few cdfs $F$ and seen to be reasonably high for unintuitive choices such as $\beta = .9, \beta = 2$, and also to be…

一致的非参数回归AI 解读

Let $(X, Y)$ be a pair of random variables such that $X$ is $\mathbb{R}^d$-valued and $Y$ is $\mathbb{R}^{d'}$-valued. Given a random sample $(X_1, Y_1), \cdots, (X_n, Y_n)$ from the distribution of $(X, Y)$, the conditional distribution $P^Y(\bullet \mid X)$ of $Y$ given $X$ can be estimated nonparametrically by $\hat{P}_n^Y(A \mid X) = \sum^n_1 W_{ni}(X)I_A(Y_i)$, where the weight function $W_n$ is of the form $W_{ni}(X) = W_{ni}(X, X_1, \cdots, X_n), 1 \leqq i \leqq n$.…

可交换随机变量的一种正依赖概念AI 解读

An $n$-variate distribution function is said to be positive dependent by mixture (PDM) if it is a mixture of independent $n$-variate distributions with equal marginals. PDM distributions arise in various contexts of reliability and other areas of statistics. We give a necessary and sufficient condition, by means of independent random variables, for an $n$-variate distribution function to be PDM. The distributions and the expectations of the order statistics of PDM and of…

次序统计量函数的重对数律AI 解读

A general law of the iterated logarithm for linear combinations of order statistics is proved. The key tools are (1) iterated logarithm convergence of the uniform empirical process $U_n$ in $\rho_q$-metrics due to B. R. James and (2) almost sure "nearly linear" bounds for the empirical distribution function. A law of the iterated logarithm for the quantile process is also established.

Glivenko–Cantelli定理与次序统计量函数的强大数定律AI 解读

A strengthened version of the Glivenko-Cantelli theorem for the uniform empirical distribution function is proved. The strengthened Glivenko-Cantelli theorem is used to establish strong laws of large numbers for linear functions of order statistics.

有限信息估计量一种修正的若干性质AI 解读

THE SMALL SAMPLE PROPERTIES of the estimators of parameters in a single equation of a system of equations have been investigated in several ways. Some of the many Monte Carlo studies that have been conducted are reviewed in Johnston [8]. Nagar [14] used expansions in powers of terms whose order in probability was T1, where T is the sample size, to obtain approximations of the small-sample behavior of the members of Theil's k-class estimators [18]. Basmann [4, 5], Kabe [9],…

洛伦兹曲线在经济分析中的应用AI 解读

The Lorenz curve relates the cumulative proportion of income units to the cumulative proportion of income received when units are arranged in ascending order of their income. In the past the curve has been mainly used as a convenient graphic device to represent the size distribution of income and wealth. In this paper the Lorenz curve technique is used as a tool to introduce distributional considerations in economic analysis. The concept has been extended and generalized to…

分布函数估计AI 解读

It is shown that the limiting distribution of any regular estimator of a continuous cdf on [0, 1] can be represented as a convolution of the Brownian bridge process with another distribution on $C\lbrack 0, 1\rbrack$. The result is related to Hajek's representation for limiting distributions of regular parametric estimators.