论文检索

摘要暂缺

删失线性回归半参数估计中的带宽选择AI 解读

Quantile and semiparametric M estimation are methods for estimating a censored linear regression model without assuming that the distribution of the random component of the model belongs to a known parametric family. Both methods require estimating derivatives of the unknown cumulative distribution function of the random component. The derivatives can be estimated consistently using kernel estimators in the case of quantile estimation and finite difference quotients in the…

两种不平等指数的大样本性质AI 解读

THIS PAPER PROVIDES the large sample properties of two inequality indices, Atkinson's (1970) index and the generalized entropy index (Cowell and Kuga (1981), Shorrocks (1984)). The large sample properties of the equally-distributed-equivalent (e.d.e.) income measures associated with these indices are also derived. The asymptotic distributions of these inequality and welfare measures allow the construction of confidence intervals and tests for differences in the measures;…

个人收入分布：新模型的构建及其对美国收入数据的应用AI 解读

Abstract This paper proposes a four‐parameter statistical model of the personalized distribution of income using the ‘income share elasticity’ approach suggested by Esteban (1986). Our proposed model includes the Singh–Maddala (1976) and Dagum (1977) distributions as special cases. The generalized beta II distribution of McDonald (1984) is also a variant of this model. It appears to give an excellent fit to US income data and its empirical performance turns out to be…

生存分布在指定年龄下的“新优于旧”性质检验AI 解读

The cumulative distribution function F, of a nonnegative random variable, is said to be new better than used of specified age t0 if F¯(x+t0)≤F¯(x)F¯(t0) for all x≥0⁠, where F¯=1-FLet We propose a class of test statistics Tk, indexed by a positive integer k, for testing the null hypothesis that F belongs to A against the alternative hypothesis that F is new better than used of specified age t0 but not in A. We compare the performance of our proposed test statistics with the…

对称性下t统计量尾概率的最优阶不等式AI 解读

An inequality for the tail probabilites of the t statistic under the hypotheses of independence and symmetry is presented and is shown to yield bounds for the upper quantiles that approach those of the normal (and hence the smallest of such bounds possible) as the corresponding upper tail area tends to 0.

删失程度对置信区间有效性的影响AI 解读

This article examines how the level of censoring affects the validity of confidence intervals constructed from an exponential maximum likelihood estimator under departures from an assumed exponential survival distribution. The motivation for this work is a simulation study by Emerson (1981) suggesting that under Weibull departures from exponentiality, validity of confidence intervals for median survival time improves as censoring increases. To see if this result holds…

删失对置信区间有效性的影响AI 解读

This article examines how the level of censoring affects the validity of confidence intervals constructed from an exponential maximum likelihood estimator under departures from an assumed exponential survival distribution. The motivation for this work is a simulation study by Emerson (1981) suggesting that under Weibull departures from exponentiality, validity of confidence intervals for median survival time improves as censoring increases. To see if this result holds…

指定年龄下生存分布的“新优于旧”性质检验AI 解读

The cumulative distribution function F, of a nonnegative random variable, is said to be new better than used of specified age t0 if F¯(x+t0)≤F¯(x)F¯(t0) for all x≥0⁠, where F¯=1-FLet We propose a class of test statistics Tk, indexed by a positive integer k, for testing the null hypothesis that F belongs to A against the alternative hypothesis that F is new better than used of specified age t0 but not in A. We compare the performance of our proposed test statistics with the…

比较估计量分布函数图形的解释AI 解读

In this paper I examine graphical comparisons of one-dimensional (or marginal) distribution functions of alternative estimators. It is shown that areas under the c.d.f. (cumulative distribution function) curve can be given a decision-theoretic interpretation as risk under a bounded absolute-error loss function. I also show that by a simple rescaling of the graph's axes, graphical areas are created which can be interpreted as risk under bounded squared-error loss. The bounded…

非稳定自回归误差下时间序列回归估计量极限分布的一般方法AI 解读

The authors consider the time series regression model where the error term follows a nonstable autoregressive process and present a general approach for delivering the limiting distribution of a normalized estimator for the autoregressive parameter. The present approach is quite straightforward and leads them to an accurate evaluation of the distribution function, unlike the other approaches suggested in the literature. The authors' methodology is illustrated and percent…

多元方差分量秩检验的分位点AI 解读

In the balanced one-way multivariate analysis of variance with random effects the likelihood ratio criterion for testing that the rank of the covariance matrix of the effect vector is not greater than a specified number is considered. The limiting distribution of −2 times the logarithm of the criterion is the distribution of the sum of squares of the positive characteristic roots of a certain random symmetric matrix. This paper presents exact and simulated quantiles of this…

偏斜总体的稳健分位数估计量AI 解读

In this study we propose quantile estimators for a variety of skewed distributions. The proposed estimators are based on the biweight estimators for symmetric populations (Horn, 1988). These achieve good coverage across a wide variety of skewed populations, even for sample sizes as small as ten.

利用辅助信息估计调查数据的分布函数与分位数AI 解读

SUMMARY Ratio and difference estimators of a population distribution function under a general sampling design are obtained, using auxiliary population information. The relative mean errors and relative mean square errors of these estimators and a model-based estimator of Chambers & Dunstan (1986) are compared through a simulation study. The advantages of the design-based estimators over the model-based estimator under model misspecifications, especially for large samples,…

极值分布指数的矩估计量AI 解读

We extend Hill's well-known estimator for the index of a distribution function with regularly varying tail to an estimate for the index of an extreme-value distribution. Consistency and asymptotic normality are proved. The estimator is used for high quantile and endpoint estimation.

极值指数估计与高分位数估计AI 解读

This paper consists of two parts. An easy proof is given for the weak consistency of Pickands' estimate for the main parameter of an extreme-value distribution. Moreover, further natural conditions are given for strong consistency and for asymptotic normality of the estimate. Next a large quantile of a distribution is estimated by a combination of extreme or intermediate order statistics. This leads to an asymptotic confidence interval.

极小极大偏差稳健回归AI 解读

This paper considers the problem of minimizing the maximum asymptotic bias of regression estimates over $\varepsilon$-contamination neighborhoods for the joint distribution of the response and carriers. Two classes of estimates are treated: (i) $M$-estimates with bounded function $\rho$ applied to the scaled residuals, using a very general class of scale estimates, and (ii) bounded influence function type generalized $M$-estimates. Estimates in the first class are obtained…

经验函数的自助法AI 解读

We develop the complete bootstrapped parallel to the asymptotic theory of weighted empirical and quantile processes. Utilizing this parallel theory, we present a general body of techniques to establish the asymptotic validity of the bootstrap method of constructing confidence bands for statistical functions. These techniques are demonstrated to be applicable to the construction of asymptotic bootstrap confidence bands for a variety of concrete functions.

广义洛伦兹曲线的渐近分布无关统计推断AI 解读

This paper provides asymtotically distribution-free statistical inference procedures for generalized Lorenz curves. Given appropriate measures of income and the income recipient unit are chosen appropriately, the tests allow consensually valid statements regarding social welfare to be made from sample data on the basis of sound inferential procedures. More generally, the results presented here can be applied to test for second degree stochastic dominance. Copyright 1989 by…

贫困测度：一个与 Theil 不平等度量相关的指数AI 解读

A major problem that arises in measuring poverty is the adequate expression, in a poverty index, of the information from the incomes of individuals below the poverty line. This article evaluates several poverty indexes on the basis of their ability to satisfy five properties desirable for a poverty index. The only index that satisfies all five properties is one related to a Theil measure of inequality. Simulations show that this index and an index related to the coefficient…

连续不变决策问题中经验分布函数的不可容许性AI 解读

Consider the classical invariant decision problem of estimating an unknown continuous distribution function $F,$ with the loss function $L(F, a) = \int(F(t) - a(t))^2\lbrack F(t) \rbrack^\alpha \lbrack 1 - F(t) \rbrack^\beta dF(t),$ and a random sample of size $n$ from $F.$ It is proved that the best invariant estimator is inadmissible when: 1. $ n > 0, - 1 < \alpha, \beta \leq 0 \text{and} -1 \leq \alpha + \beta.$ 2. $ n > 0, -1 < \alpha = \beta \leq - \frac{1}{2}.$ 3. $ n > 1, (\mathrm{i}) \alpha = -1 \text{and} \beta = 0, \text{or} (\mathrm{ii}) \alpha = 0 \text{and} \beta = -1.$…

若干多元正态混合分布的渐近展开及误差界AI 解读

This paper deals with the distribution of $\mathbf{X} = \sum^{1/2}\mathbf{Z}$, where $\mathbf{Z}: p \times 1$ is distributed as $N_p(0, I_p), \sum$ is a positive definite random matrix and $\mathbf{Z}$ and $\sum$ are independent. Assuming that $\sum = I_p + BB'$, we obtain an asymptotic expansion of the distribution function of $\mathbf{X}$ and its error bound, which is useful in the situation where $\sum$ tends to $I_p$. A stronger version of the expansion is also given.…

刀切法方差估计的一般理论AI 解读

The delete-1 jackknife is known to give inconsistent variance estimators for nonsmooth estimators such as the sample quantiles. This well-known deficiency can be rectified by using a more general jackknife with $d$, the number of observations deleted, depending on a smoothness measure of the point estimator. Our general theory explains why jackknife works or fails. It also shows that (i) for "sufficiently smooth" estimators, the jackknife variance estimators with bounded $d$…

估计量与分布的离散程度AI 解读

Arbitrary, possibly randomized estimators of a one-dimensional parameter are considered. It is shown that suitable averages of their distribution functions are more spread out than particular distribution functions, which are defined in terms of the weight functions by which the averages are taken over the parameter space and in terms of the family of distributions for the random quantity on which the estimators are based. In this way bounds are provided for the performance…