Bootstrap of the offspring mean in the critical process with a non-stationary immigration

In applications of branching processes, usually it is hard to obtain samples of a large size. Therefore, a bootstrap procedure allowing inference based on a small sample size is very useful. Unfortunately, in the critical branching process with stationary immigration the standard parametric bootstrap is invalid. In this paper, we consider a process with non-stationary immigration, whose mean and variance vary regularly with nonnegative exponents α and β, respectively. We prove that 1+2α is the threshold for the validity of the bootstrap in this model. If β<1+2α, the standard bootstrap is valid and if β>1+2α it is invalid. In the case β=1+2α, the validity of the bootstrap depends on the slowly varying parts of the immigration mean and variance. These results allow us to develop statistical inferences about the parameters of the process in its early stages.     

非参数模型均值函数结构变点的Bootstrap检测

本文检测非参数回归模型均值函数结构变点,针对均值函数跃度的长期均值为零时,基于残量的CUSUM统计量对均值函数结构变点检验无效的问题,本文提出了一种基于均值函数的核估计的检验统计量,得到统计量在原假设和备择假设下的极限分布,并构造Bootstrap方法对非参数回归模型均值函数结构变点进行检验,证明了检验和估计的一致性;模拟结果表明本文方法明显优于已有方法。     

A comparison of approaches for valid variogram achievement

Summary  Variogram estimation is a major issue for statistical inference of spatially correlated random variables. Most natural empirical estimators of the variogram cannot be used for this purpose, as they do not achieve the conditional negative-definite property. Typically, this problem’s resolution is split into three stages:empirical variogram estimation;valid model selection; andmodel fitting. To accomplish these tasks, there are several different approaches strongly defended by their authors. Our work’s main purpose was to identify these approaches and compare them based on a numerical study, covering different kind of spatial dependence situations. The comparisons are based on the integrated squared errors of the resulting valid estimators. Additionally, we propose an easily implementable empirical method to compare the main features of the estimated variogram function. Partially supported by Grants BFM2002-03213 and PGIDIT03PXIC20702PN from Ministerio de Ciencia y Tecnologia, Spain in collaboration with Foundation for the Regional European Development and Xunta de Galicia, Spain.     

On the Local Time of the Weighted Bootstrap and Compound Empirical Processes

This article is mainly concerned with the local times of the weighted bootstrap process. We prove a strong approximation theorem for the local time of the weighted bootstrap process by the local time of a Brownian bridge. We consider also the local time of the compound empirical processes that can be seen, asymptotically, as the local time of the convolution of two independent Gaussian processes.     

A comparison of various methods for obtaining confidence intervals for the design lowflow values of streams and rivers

This paper describes an intriguing use of two relatively new statistical procedures, the bootstrap and non-stationary Markov modelling, to obtain confidence intervals for the design low-flow parameter, of great interest to hydrologists. The procedure described is applied to the stream-flow data gathered over more than 50 years from six gauging sites in Georgia, and is found to yield confidence intervals which are typically shorter than those given by traditional methods.     

BOOTSTRAP MAXIMUM LIKELIHOOD ESTIMATION OF THE PARAMETER IN SPECTRAL DENSITY OF STATIONARY PROCESSES

ＢＯＯＴＳＴＲＡＰ　ＭＡＸＩＭＵＭＬＩＫＥＬＩＨＯＯＤＥＳＴＩＭＡＴＩＯＮＯＦＴＨＥＰＡＲＡＭＥＴＥＲＩＮＳＰＥＣＴＲＡＬＤＥＮＳＩＴＹＯＦＳＴＡＴＩＯＮＡＲＹ　ＰＲＯＣＥＳＳＥＳＹＵＤＡＮ（于丹）（ＩｎｓｔｉｔｕｔｅｏｆＳｙｓｔｅｍｓＳｃｉｅｎｃｅ...     

基于Bootstrap法的样本函数条件极值的方差估计(英文)

对样本函数条件极值中γ2的估计进行了探讨,给出了γ2估计的一种方法—自助法,并对所得到的统计量的性质进行了分析.     

未决赔款准备金评估的对数正态模型及其预测分布的Bootstrap实现

目前在我国精算实务中对未决赔款准备金评估的不确定性风险逐渐重视,对不确定性加以度量显得很有必要.在以往关于未决赔款准备金的不确定性研究中,大多集中于预测均方误差.从数值角度看,如果应用随机模拟的方法,能得到未决赔款准备金完整的预测分布,那么就可以由该分布得到各个分位数以及相关的分布度量,对准备金负债评估的准确性和充足性具有重要的参考价值.研究的对数正态模型是未决赔款准备金评估中的分布模型之一,它假设累计赔款单个进展因子服从对数正态分布,进而将参数Bootstrap方法和非参数Bootstrap方法应用于对数正态模型中,得到了未决赔款准备金的预测分布,并通过精算实务中的数值实例加以实证分析.数值实例由当前国际上日益流行的统计软件R加以实现.     

The Latent Scale Covariogram: A Tool for Exploring the Spatial Dependence Structure of Nonnormal Responses

When modeling spatially distributed normal responses Y_i in terms of vectors x_i of explanatory variables, one may fit a linear model assuming independence, and then use the empirical variogram of the residuals to determine an appropriate parametric form for the autocorrelation function. Suppose, however, that the responses are not normally distributed—for example, Poisson or Bernoulli. One may model spatial dependence using a hierarchical generalized linear model in which, conditional on a latent Gaussian field Z = {Z_i}, the Y_i have independent distributions from the exponential family, with an appropriate link function connecting their conditional means with the linear predictors x^t_iβ + Z_i. The question then is how to determine an appropriate model for the autocorrelation function of Z. The empirical variogram of the Y_i is no longer appropriate, since (unless the link function is the identity) it is on the wrong scale. We propose here an alternative, the latent scale covariogram, whose graph reflects the autocorrelation structure of the underlying normal field. We illustrate its use on several real datasets, together with a simulated dataset, and obtain results quite different from those obtained using the variogram. Supplementary materials for this article are available online.     

多个偏正态总体共同位置参数的Bootstrap置信区间

该文基于Bootstrap 方法研究多个偏正态总体共同位置参数的区间估计和假设检验问题.首先,分别给出未知参数的矩估计和极大似然估计.其次,将徐礼文[1]对多个正态总体共同均值的探讨推广到多个偏正态总体,进而构造共同位置参数的Bootstrap 置信区间和Bootstrap检验统计量.Monte Carlo模拟结果表明...     

一定条件下样本函数极值的重采样方法

本文对一定条件下样本函数极值的重采样方法进行了研究,给出了γ~2估计的几种方法,包括减-d折刀法、减-1折刀法和自助法；并对得到的统计量的性质进行了分析．     

基于极大似然的异方差多正态总体均值的参数Bootstrap检验

本文考虑了异方差下多正态总体均值的检验问题。传统检验方法多为近似分布检验,且受总体数目及其样本量的影响较为严重,只有在总体数目较少、样本量适中或较大时才能很好的控制第一类错误。较近提出的参数bootstrap检验有效解决了在总体数目较多时检验的任意性,但在总体样本量都较小时,检验控制第一类错误倾向保守,或总体中存在个别样本量较少时犯第一类错误概率上升。本文从极大似然的角度推导出具有修正权重的极大似然检验统计量,并与bootstrap方法有效的结合,得到新的参数bootstrap检验方法。通过Monte Carlo模拟第一类错误和检验的势与Welch检验和广义F检验进行比较,结果表明本文提出的极大似然参数bootstrap检验在总体数目较多和存在小样本量时,均能很好地控制第一类错误,同时且有较好的势,适用范围更加广泛。     

两个和K个分布函数相等的自助法检验(英文)

两个和Ｋ 个分布函数相等的检验在统计领域中,长期以来一直受到关注．为了克服高维空间中数据点的稀疏性,并且对一般情况进行处理,我们提出了几个投影追踪类型的统计量,并得到了这些统计量的极限分布的一些结果．对一些自助法逼近的性质进行了研究．更进一步地,由于计算的原因,对统计量的逼近,我们采用了数论方法,并进行了一些模拟试验     

Some consequences of estimating parameters for the M/M/1 queue

An important interface between stochastic models and actual systems comes in estimating values for model parameters using “real world” data. This interface between models and systems is studied for one of the most elementary stochastic systems, the M/M/1 queue. Estimating arrival rates and service rates results in a notable discrepancy between the state distribution for the model (estimated parameters) and the state distribution for the actual system (known parameters). Also, the expected number of customers in the model is infinite regardless of the (unknown) value of the actual traffic intensity. The truth of this assertion is obvious if one allows estimated traffic intensities to equal or exceed one. However, it is shown that the mean for the model is infinite even if the estimated traffic intensity is restricted to be strictly less than one.     

Inner and outer bounds for the solution set of parametric linear systems

Consider linear systems involving affine-linear dependencies on interval parameters. Presented is a free C-XSC software implementing a generalized parametric fixed-point iteration method for verified enclosure of the parametric solution set. Some specific features of the corresponding algorithm concerning sharp enclosure of the contracting matrix and inner approximation of the solution enclosure are discussed.     

Statistics of extremes for IID data and breakthroughs in the estimation of the extreme value index: Laurens de Haan leading contributions

In the last decades there has been a shift from the parametric statistics of extremes for IID random variables, based on the probabilistic asymptotic results in extreme value theory, towards a semi-parametric approach, where the estimation of the right tail-weight, under a quite general framework, is of major importance. After a brief presentation of classical Gumbel’s block methodology and of later improvements in the parametric framework (multivariate and multi-dimensional extreme value models for largest observations and peaks over threshold approaches), we present a coordinated overview, over the last three decades, of the developments on the estimation of the extreme value index under a semiparametric framework. Laurens de Haan has been one of the leading scientists in the field, (co-)author of many seminal ideas, that he generously shared with dozens (literally) of colleagues and students, thus achieving one of the main goals in a scientist’s life: he gathered around him a bunch of colleagues united in the endeavour of building knowledge. The last section is a personal tribute to Laurens, who fully lives his ideal that co-operation is the heart of Science. To Laurens de Haan, a token of friendship.     

On the parameterization of the CreditRisk model for estimating credit portfolio risk

The CreditRisk⁺ model is one of the industry standards for estimating the credit default risk for a portfolio of credit loans. The natural parameterization of this model requires the default probability to be apportioned using a number of (non-negative) factor loadings. However, in practice only default correlations are often available but not the factor loadings. In this paper we investigate how to deduce the factor loadings from a given set of default correlations. This is a novel approach and it requires the non-negative factorization of a positive semi-definite matrix which is by no means trivial. We also present a numerical optimization algorithm to achieve this.     

On a generalization of Morisita's model for estimating the habitat preference

The Morisita's model for estimating the habitat preference by the ant lionsGenuroides japonicus is generalized by introducing, in addition to the environmental densitiesa andb, a repulsivity parameter . The probability function of the numberL _n of individuals choosing fine sand to settle when a total ofn ant lions are introduced is examined. A heuristic and the minimum chi-square methods for estimating the parametersa, b and are discussed.