An immune algorithm with stochastic aging and kullback entropy for the chromatic number problem

We present a new Immune Algorithm, IMMALG, that incorporates a Stochastic Aging operator and a simple local search procedure to improve the overall performances in tackling the chromatic number problem (CNP) instances. We characterize the algorithm and set its parameters in terms of Kullback Entropy. Experiments will show that the IA we propose is very competitive with the state-of-art evolutionary algorithms.     

Estimating population size with truncated sampling

Let X₁, X₂,…,X_n be independent, indentically distributed random variables with density f(x,θ) with respect to a σ-finite measure μ. Let R be a measurable set in the sample space X. The value of X is observable if X ? (X?R) and not otherwise. The number J of observable X’s is binomial, N, Q, Q = 1?P(X ? R). On the basis of J observations, it is desired to estimate N and θ. Estimators considered are conditional and unconditional maximum likelihood and modified maximum likelihood using a prior weight function to modify the likelihood before maximizing. Asymptotic expansions are developed for the [Ncirc]’s of the form [Ncirc] = N + α√N + β + o_p(1), where α and β are random variables. All estimators have the same α, which has mean 0, variance σ² (a function of θ) and is asymptotically normal. Hence all are asymptotically equivalent by the usual limit distributional theory. The β’s differ and Eβ can be considered an “asymptotic bias”. Formulas are developed to compare the asymptotic biases of the various estimators. For a scale parameter family of absolutely continuous distributions with X = (0,∞) and R = (T,∞), special formuli are developed and a best estimator is found.     

多孔介质中可压缩混溶驱动问题的特征：混合元方法

本文考虑二维一般有界区域中的多孔介质同可压缩混溶动问题的数值解方法，给出了全离散特征－混合元格，证明了格式的唯一可解性，得到最佳Ｈ－模误差估计。     

Assessment of Uncertainty in High Frequency Data: The Observed Asymptotic Variance

The availability of high frequency financial data has generated a series of estimators based on intra‐day data, improving the quality of large areas of financial econometrics. However, estimating the standard error of these estimators is often challenging. The root of the problem is that traditionally, standard errors rely on estimating a theoretically derived asymptotic variance, and often this asymptotic variance involves substantially more complex quantities than the original parameter to be estimated. Standard errors are important: they are used to assess the precision of estimators in the form of confidence intervals, to create “feasible statistics” for testing, to build forecasting models based on, say, daily estimates, and also to optimize the tuning parameters. The contribution of this paper is to provide an alternative and general solution to this problem, which we call Observed Asymptotic Variance. It is a general nonparametric method for assessing asymptotic variance (AVAR). It provides consistent estimators of AVAR for a broad class of integrated parameters Θ = ∫ θ_t dt, where the spot parameter process θ can be a general semimartingale, with continuous and jump components. The observed AVAR is implemented with the help of a two‐scales method. Its construction works well in the presence of microstructure noise, and when the observation times are irregular or asynchronous in the multivariate case. The methodology is valid for a wide variety of estimators, including the standard ones for variance and covariance, and also for more complex estimators, such as, of leverage effects, high frequency betas, and semivariance.     

Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps

Abstract. We consider a stochastic process driven by diffusions and jumps. Given a discrete record of observations, we devise a technique for identifying the times when jumps larger than a suitably defined threshold occurred. This allows us to determine a consistent non‐parametric estimator of the integrated volatility when the infinite activity jump component is Lévy. Jump size estimation and central limit results are proved in the case of finite activity jumps. Some simulations illustrate the applicability of the methodology in finite samples and its superiority on the multipower variations especially when it is not possible to use high frequency data.     

局部环上典型群的非双曲型

引入域上典型群的生成问题所得的成果；对局部环R上典型群生成问题研究，构造度量函数及一平延，为局部环R上典型群向域F上的典型群导入，给出典型群的非双曲型．     

利用最小化代价函数方法实现多窗口谱分析

利用最小化代价函数的方法推导了一种谱分析的多窗口。性能分析的结果表明，此方法与离散长球序列多窗口谱分析方法具有相当的估计偏差与方差性能。与离散长球序列多窗口相比，此方法得到的多窗口具有直观的解析表达式而无须求解矩阵的特征分解问题，因而具有较小的计算量。通过对离散白噪声与ＡＲ过程进行的多窗口谱分析对比实验，验证了此方法的有效性和正确性。     

大数幂剩余的二进制冗余数Montgomery算法

介绍了大数幂剩余的Montgomery算法,提出了基于二进制冗余数的大数幂剩余Montgomery算法模型。理论分析表明,采用二进制冗余数可减少乘法的进位传播,同时使算法的迭代步数减少17.2%。进一步提高了大数幂剩余的运算速度。     

聚并苯和氯代聚并苯同系分子的总能量与同系序数的相关性研究

聚并苯和氯代聚并苯同系分子的总能量与同系序数之间满足下列相关方程ET=aN b,N =2n 1 ,R≈ 1 ,N为同系序数 ,n是苯环的结构单元数 .本文的计算值与文献值吻合 .     

Proof of Toft's Conjecture: Every Graph Containing No Fully Odd K4 is 3-Colorable

A fully odd K₄ is a subdivision of K₄ such that each of the six edges of the K₄ is subdivided into a path of odd length. In 1974, Toft conjectured that every graph containing no fully odd K₄ can be vertex-colored with three colors. The purpose of this paper is to prove Toft's conjecture.