毛新杨×毛白杨AFLP分子遗传图谱

利用毛新杨×毛白杨的杂交群体构建了毛新杨×毛白杨的AFLP分子遗传图谱,这个群体对杨树溃疡病的抗性是正态分布。本实验使用AFLP分子标记技术对这一构图群体进行了分析,共选用了19对PstI/MseI引物和4对EcoRI/MseI引物,得到标记662个,其中3∶1标记占43 2%,异倍标记占14 5%,偏分离标记(P<0 05)占48 8%。在双亲整合的图谱中,239个标记形成22个含4个以上标记的连锁群,总图距4418cM,标记间的平均图距是18 5cM。图中还有8个重复位点和7个只与连锁群中的某一个标记连锁,但却无法加入这一连锁群的标记,这可能是由染色体的同源性造成的。此外还得到15个属于双亲共有的只有2～3个标记的小连锁群,13个父本独有的连锁群和21个母本独有的连锁群。

The Clinical Analysis of Endogenous Endophthalmitis

Purpose: To study the clinical characteristics, therapeutic efficacy and investigate pro-gnostic factors of endogenous endophthalmitis. Methods: Twenty-eight cases (28 eyes) of endogenous endophthalmitis were surveyed retrospectively. The clinical characteristics, primary infection foci, predisposing systemic disease, complications, pathogens examination, therapeutic options and efficacy were analysed. Results: The endogenous endophthalmitis occurred more frequently in the right eye than in the left one. The respiratory tract was the most common primary foci. The positive rate of pathogens culture was higher in vitreous sample than that in other tissues. Cataract and retinal detachment were the common complications. The visual improvement and infection control were achieved in 13 eyes (46.43%). These 13 patients received treatment (3.77±2.49)days after onset of endophthalmitis being much earlier than that of others [(10.13±4.98)days, P=0.002]. The prognosis was relevant to the type of the disease. The anterior segment inflammation type(anterior type) had better prognosis than posterior segment inflammation type(posterior type) and that of inflammation in both parts(mix type) (P < 0.05). There were no significant relation between the prognosis and the age, predisposing systemic disease, vitreous antibiotic injection and vitrectomy (P > 0.05).Conclusions: Endogenous endophthalmitis is a vital ocular emergency. Early diagnosis and effective treatment combination with systemic and local antibiotics are of significant value. The anterior type is prone to have better outcome than the others.

GENERAL MINIMAX ESTIMATORS ON THE LOCATION MATRIX OF A MIXTURE OF NORMALS

This paper considers the estimate problem on the mean matrix of mixture of normals. In order to evaluate estimators of the mean matrix, a fundamental frame of Φ-(general) decision problem is established. Under the frame, a class of Φ-minimax estimators are constructed.

Climate Change Signal Analysis for Northeast Asian Surface Temperature

Climate change detection, attribution, and prediction were studied for the surface temperature in the Northeast Asian region using NCEP/NCAR reanalysis data and three coupled-model simulations from ECHAM4/OPYC3, HadCM3, and CCCma GCMs (Canadian Centre for Climate Modeling and Analysis general circulation model). The Bayesian fingerprint approach was used to perform the detection and attribution test for the anthropogenic climate change signal associated with changes in anthropogenic carbon dioxide (CO2) and sulfate aerosol (SO42-) concentrations for the Northeast Asian temperature. It was shown that there was a weak anthropogenic climate change signal in the Northeast Asian temperature change. The relative contribution of CO2 and SO42- effects to total temperature change in Northeast Asia was quantified from ECHAM4/OPYC3 and CCCma GCM simulations using analysis of variance. For the observed temperature change for the period of 1959-1998, the CO2 effect contributed 10%-21% of the total variance and the direct cooling effect of SO42- played a less important role (0%-7%) than the CO2 effect. The prediction of surface temperature change was estimated from the second CO2+SO42- scenario run of ECHAM4/OPYC3 which has the least error in the simulation of the present-day temperature field near the Korean Peninsula. The result shows that the area-mean surface temperature near the Korean Peninsula will increase by about 1.1° by the 2040s relative to the 1990s.

A Generalized Information Criterion for Parameters under an Umbrella Order Restriction

The detection of the configuration of parameters is one of the most important problems in statistical studies. It is well known that the Akaike’s information criterion (AIC) is a key tool for this problem

门限自回归模型条件异方差的Kolmogorov-smirnov检验

门限自回归模型被广泛地用于许多领域.当建立或使用这类模型时,一个重要问题是需要知道是否存在条件异方差.在本文中,我们对这个问题提出一个非参数检验.检验的大样本理论被给出.我们还通过数值模拟研究了检验方法的有限样本性质.结果表示检验有好的功效.经验百分位点还被给出.

随机删失下乘积限过程和累积失效率过程振动模的局部渐近性

在随机删失下研究了乘积限过程和累积失效率过程的振动模的局部性质 .给出了这两个过程的振动模的重对数律 ,并应用这些结果得到了几种核密度估计和Bahadur

THE TRANSITION PROBABILITY MATRIX OF A MARKOV CHAIN MODEL IN AN ATM NETWORK

In this paper we consider a Markov chain model in an ATM network, which has been studied by Dag and Stavrakakis. On the basis of the iterative formulas obtained by Dag and Stavrakakis, we obtain the explicit analytical expression of the transition probability matrix. It is very simple to calculate the transition probabilities of the Markov chain by these expressions. In addition, we obtain some results about the structure of the transition probability matrix, which are helpful in numerical calculation and theoretical analysis.

LIMIT THEOREMS AND OPTIMAL DESIGN WITH ADAPTIVE URN MODELS

In this paper we study urn model, using some available estimates of successes probabilities, and adding particle parameter, we establish adaptive models. We obtain some strong convergence theorems, rates of convergence, asymptotic normality of components in the urn, and estimates. With these asymptotical results, we show that the adaptive designs given in this paper are asymptotically optimal designs.

DISTRIBUTION FREE LAWS OF THEITERATED LOGARITHM FOR KERNELESTIMATOR OF REGRESSION FUNCTIONBASED ON DIRECTIONAL DATADISTRIBUTION FREE LAWS OF THEITERATED LOGARITHM FOR KERNELESTIMATOR OF REGRESSION FUNCTIONBASED ON DIRECTIONAL DATA

The authors derive laws of the iterated logarithm for kernel estimator of regression function based on directional data. The results are distribution free in the sense that they are true for all distributions of design variable.

Detecting Change Points in Polynomial Regression Models with an Application to Cable Data Sets

In this paper, the Schwarz Information Criterion (SIC) is used to detect the change points in polynomial regression models. Switching quadratic regression models with same amount of model deviation and switching polynomial regression models with different amount of model deviation for different segments of regression are considered. The number of separate regimes and their corresponding regression orders are assume to be known. The method is then applied to cable data sets and the change points are successfully detected.

A Study of the Equivalence of the BLUEs between a Partitioned Singular Linear Model and Its Reduced Singular Linear Models

Consider the partitioned linear regression model and its four reduced linear models, where y is an n × 1 observable random vector with E(y) = Xβ and dispersion matrix Var(y) = σ2 V, where σ2 is an unknown positive scalar, V is an n × n known symmetric nonnegative definite matrix, X = (X 1 : X 2) is an n×(p+q) known design matrix with rank(X) = r ≤ (p+q), and β = (β′ 1: β′2 )′ with β1 and β2 being p×1 and q×1 vectors of unknown parameters, respectively. In this article the formulae for the differences between the best linear unbiased estimators of M 2 X 1β1under the model and its best linear unbiased estimators under the reduced linear models of are given, where M 2 = I -X 2 X 2 + . Furthermore, the necessary and sufficient conditions for the equalities between the best linear unbiased estimators of M 2 X 1β1 under the model and those under its reduced linear models are established. Lastly, we also study the connections between the model and its linear transformation model.

Bootstrap Approximation to the Distribution of M-estimates in a Linear Model

The authors establish the approximations to the distribution of M-estimates in a linear model by the bootstrap and the linear representation of bootstrap M-estimation, and prove that the approximation is valid in probability 1. A simulation is made to show the effects of bootstrap approximation, randomly weighted approximation and normal approximation.

Asymptotics of Huber-Dutter Estimators for Partial Linear Model with Nonstochastic Designs

For partial linear model Y = X~τβ_0 + g_0(T) + ε with unknown β_0 ∈ R^dand an unknown smooth function g_0, this paper considers the Huber-Dutter estimators of β_0, scaleσ for the errors and the function g_0 respectively, in which the smoothing B-spline function isused. Under some regular conditions, it is shown that the Huber-Dutter estimators of β_0 and σ areasymptotically normal with convergence rate n^(-1/2) and the B-spline Huber-Dutter estimator of g_0achieves the optimal convergence rate in nonparametric regression. A simulation study demonstratesthat the Huber-Dutter estimator of β_0 is competitive with its M-estimator without scale parameterand the ordinary least square estimator. An example is presented after the simulation study.

Gelation of a Reversible Markov Process of Polymerization

Abstract In this paper a reversible Markov process as a chemical polymers reaction of two types of monomers is defined. By analyzing the partition functions of the process we obtain three different distributions of the average molecular weight, depending on the value of strength of the fragmentation reaction, and prove that a gelation of the process will occur in the thermodynamic limit.

A KULLBACK-LEIBLER EMPIRICAL LIKELIHOOD INFERENCE FOR CENSORED DATA

In this paper, two kinds of Kullback-Leibler criteria with appropriate constraints are proposed to construct empirical likelihood confidence intervals for the mean of right censored data. It is shown that one of the criteria is equivalent to Adimari’s(1997) procedure, and the other shares the same asymptotic behavior.

Sharp Error Estimate for Maximum Likelihood Estimator of Nonstationary Diffusion Processes

We consider the maximum likelihood estimator of the unknown parameter in aclass of nonstationary diffusion processes. We give further a precise estimate for the error of theestimator.