带有误差变量混合分布模型的估计

在许多实际同题中，存在一些不可直接观测的变量，对此统计学家们提出了反卷积和混合分布模型来解决这一变量的分布的估计问题。本文对这一问题采用bootstrap模拟方法得出分布函数的估计，并进一步建立该分布函数的非参bootstrap百分位区间，在数值试验中将我们的处理方式与传统的EM算法得到的分布估计和正态逼近区间作比较，数值结果表明用bootstrap模拟方法得到的准确度更好，数值效果更理想。     

A bootstrap approach to model checking for linear models under length-biased data

In this paper, we propose two bootstrap-based model checking tests for a parametric linear model when data are affected by length-bias. These tests are based on the measure of the discrepancy between nonparametric and parametric estimators for the regression function when the data are drawn under a length-biased mechanism. We consider two different discrepancy measures: the supremum and the integral of the quadratic difference between the parametric and nonparametric estimators.     

Bootstrapping the mode

The problem of constructing bootstrap confidence intervals for the mode of a density is considered. Estimates of the mode are derived from kernel density estimates based on fixed and data-dependent bandwidths. The asymptotic validity of bootstrap techniques to estimate the sampling distribution of the estimates is investigated. In summary, the results are negative in the sense that a straightforward application of a naive bootstrap yields invalid inferences. In particular, the bootstrap fails if resampling is done from the kernel density estimate. On the other hand, if one resamples from a smoother kernel density estimate (which is necessarily different from the one which yields the original estimate of the mode), the bootstrap is consistent. The bootstrap also fails if resampling is done from the empirical distribution, unless the choice of bandwidth is suboptimal. Similar results hold when applying bootstrap techniques to other functionals of a density.     

Quantile Processes in the Presence of Auxiliary Information

We employ the empirical likelihood method to propose a modified quantile process under a nonparametric model in which we have some auxiliary information about the population distribution. Furthermore, we propose a modified bootstrap method for estimating the sampling distribution of the modified quantile process. To explore the asymptotic behavior of the modified quantile process and to justify the bootstrapping of this process, we establish the weak convergence of the modified quantile process to a Gaussian process and the almost-sure weak convergence of the modified bootstrapped quantile process to the same Gaussian process. These results are demonstrated to be applicable, in the presence of auxiliary information, to the construction of asymptotic bootstrap confidence bands for the quantile function. Moreover, we consider estimating the population semi-interquartile range on the basis of the modified quantile process. Results from a simulation study assessing the finite-sample performance of the proposed semi-interquartile range estimator are included.     

Cascade reactions leading to the mechanism of action of vinaxanthone and xanthofulvin,natural products that drive nerve repair

The natural products vinaxanthone and xanthofulvin promote regeneration in animal models of spinal cord injury and corneal transplant. However, inhibition of the initially described biological target of these compounds, semaphorin 3A, does not fully account for the recovery demonstrated in vivo following administration of the natural products. Through chemical synthesis substantial quantities of both natural products have been accessed with early reaction development paving the way for synthesizing both compounds. The success of a model system, first disclosed herein, translated to the syntheses of both natural products. Following from this we also report for the first time the discovery of a new target of the natural products, the succinate receptor 1 (SUCNR1). Both natural products function as positive allosteric modulators of SUCNR1. As the first known allosteric modulators of SUCNR1, the compounds represent powerful new tools to understand the pharmacology of SUCNR1 and its control of growth and cellular defense.     

A note on bootstrapping the variance of sample quantile

Summary Letm _{n, p} denote thep-th quantile based onn observations and let λ _p denote the population quantile. In this paper consistency of the bootstrap estimate of variance of is established.     

青海油砂矿的物理化学特性

油砂矿的物理、化学性质是其开发利用的关键因素之一 ;作者利用多种分析手段 ,揭示了青海出露油砂的特殊有机物化学组成与分布及其物理性质 ,其轻质组分含量很高 ,饱和烃含量高达近一半 ,而胶质、沥青质重组分含量低 (<38 % ) ,H和C原子比甚高 ,直链烷烃分布规整 ,主要集中在C19～C37 范围 ,物理参数处在普通重油范围内 ;该种物理、化学性质独特的出露油砂在全球为首次发现 ,是青海油砂矿特殊的地理地质环境所造成的 ,作者建议其开采宜采用钻井采油和露天开采依次进行的新组合方法     

Statistical validation of classification and calibration models using bootstrapped Latin partitions

Unbiased evaluation of classification and calibration methods is important, especially as these methods are applied to increasingly complex data sets that are under-determined. Precision bounds, such as confidence intervals, are required for interpreting any experimental result. Using bootstrapped Latin partitions to evaluate classification and calibration models, bounds on the average predictions were obtained. These bounds characterize sources of variation attributed to building the model and the composition of the training set with respect to the test set. Furthermore, precision bounds on the average of the model-variable loadings allow the significance of characteristic features to be estimated. The procedure for bootstrapped Latin partitions is given and demonstrated with synthetic data sets for classification using linear discriminant analysis and fuzzy rule-building expert systems, and for calibration using partial least squares regression with one and three properties. All analyses were implemented on a personal computer with the longest evaluation requiring 6-h processing time. Analysis of variance and matched sample t-tests were also used to demonstrate the statistical power of these tests.     

A convenient cyclopropanation process of oxindoles via bromoethylsulfonium salt

A practical convenient conversion of oxindoles into the corresponding spirocyclopropyl oxindoles is achieved efficiently using bromoethylsulfonium salt, which is easily prepared on a large scale and is stable crystalline. This reaction of bromoethylsulfonium salt with different substituted unprotected oxindoles proceeded under mild condition and provided moderate yields.     

二维指数信号模型中参数Bootstrap估计的强相合性

本文主要研究了在统计信号处理当中具有广泛应用的二维带白噪声指数信号模型中参数估计的Bootstrap逼近, 借助于回归模型中Bootstrap逼近的构造方法, 给出了二维指数信号模型参数的自助估计, 并证明了自助估计具有强相合性. 最后采用了Monte-Carlo法对所提的方法进行随机模拟, 模拟的结果表明当噪声不服从正态分布时, Bootstrap方法的估计效果优于最小二乘估计.