运用基因型统计量对数量性状位点进行关联分析

随着基因分型技术的不断发展,遗传学家可以获得大量遗传标记的基因型和单体型数据,这为鉴定人类复杂疾病基因提供了前所未有的机会。当不能直接获得单体型数据时,可以使用基因型数据的统计方法来进行关联分析．使用基因型数据对疾病基因进行关联分析的统计方法可以扩充到定位数量性状位点（QTL）。本文扩充了对疾病基因进行关联分析的主成份分析统计量PG咒和熵统计量％。到数量性状,利用选择基因型对QTL进行关联分析。计算机模拟考察了两个统计量的I型错误率．基于10个遗传性血色病（Hereditaryhaemochromatosis）单体型频率的计算机模拟调查了两个统计量的统计功效．结果表明两个统计量PCTt和TGE可以有效地对QTL进行关联分析．     

Slow and fast scales for superprocess limits of age-structured populations

A superprocess limit for an interacting birth-death particle system modeling a population with trait and physical age-structures is established. Traits of newborn offspring are inherited from the parents except when mutations occur, while ages are set to zero. Because of interactions between individuals, standard approaches based on the Laplace transform do not hold. We use a martingale problem approach and a separation of the slow (trait) and fast (age) scales. While the trait marginals converge in a pathwise sense to a superprocess, the age distributions, on another time scale, average to equilibria that depend on traits. The convergence of the whole process depending on trait and age, only holds for finite-dimensional time-marginals. We apply our results to the study of examples illustrating different cases of trade-off between competition and senescence.     

Haplotyping populations by pure parsimony based on compatible genotypes and greedy heuristics

The population haplotype inference problem based on the pure parsimony criterion (HIPP) infers an m × n genotype matrix for a population by a 2m × n haplotype matrix with the minimum number of distinct haplotypes. Previous integer programming based HIPP solution methods are time-consuming, and their practical effectiveness remains unevaluated. On the other hand, previous heuristic HIPP algorithms are efficient, but their theoretical effectiveness in terms of optimality gaps has not been evaluated, either. We propose two new heuristic HIPP algorithms (MGP and GHI) and conduct more complete computational experiments. In particular, MGP exploits the compatible relations among genotypes to solve a reduced integer linear programming problem so that a solution of good quality can be obtained very quickly; GHI exploits a weight mechanism to selects better candidate haplotypes in a greedy fashion. The computational results show that our proposed algorithms are efficient and effective, especially for solving cases with larger recombination rates.     

单体型装配问题及其算法

单核苷酸多态性(SNP)单体型装配问题就是从给定的来自某人染色体的SNP片段中去除错误,重构出尽可能与原来片段一致的单体型.这个问题有几个不同的模型最少片段去除(MFR)问题,最少SNP去除(MSR)问题以及最少错误纠正(MEC)问题.前两个问题的复杂性与算法已有一些学者研究过.第三个问题已被证明是NP完全问题,但这个问题的实际算法还没有.该文对MEC问题给出了一个分支定界算法,这个算法能得到问题的全局最优解.通过这个算法对实际数据的计算说明了MEC模型的合理性,即在一定条件下,通过修正最少的错误重构出的单体型确实是真实的单体型.由于分支定界算法对这样一个NP完全问题不能在可接受的时间内解规模较大的问题,文中又给出了求解MEC问题的两个基于动态聚类的算法,以便对规模较大的问题在可接受的时间内得到近似最优解.数值实际表明这两个算法很快,很有效.这两个算法总能得到与分支定界找到的全局最优解很接近的近似最优解.鉴于MEC问题是NP完全的,这两个算法是有效的、实际的算法.     

基于主成分分析下候选基因关联检验的数学模型

对候选基因的关联检验,都是针对性状在候选基因内使用多个SNP标记,并通过检验SNP单倍型来完成的,众所周知,多标记单倍型方法往往要比单标记方法表达出更多的信息,但是,单倍型的数量往往会随着所标记的SNP的数目增多而急剧的增加,这又会大大增加检验统计量的自由度,使用统计学中的主成分分析法来降低单倍型空间的维数,并构造关联检验来检验一个数量性状与多个单倍型的关联情况,模拟结果显示,此检验方法是较合理的.     

Asymptotic distributions in the projection pursuit based canonical correlation analysis

In this paper, associations between two sets of random variables based on the projection pursuit (PP) method are studied. The asymptotic normal distributions of estimators of the PP based canonical correlations and weighting vectors are derived.     

Quasi-stationary distributions for structured birth and death processes with mutations

We study the probabilistic evolution of a birth and death continuous time measure-valued process with mutations and ecological interactions. The individuals are characterized by (phenotypic) traits that take values in a compact metric space. Each individual can die or generate a new individual. The birth and death rates may depend on the environment through the action of the whole population. The offspring can have the same trait or can mutate to a randomly distributed trait. We assume that the population will be extinct almost surely. Our goal is the study, in this infinite dimensional framework, of the quasi-stationary distributions of the process conditioned on non-extinction. We first show the existence of quasi-stationary distributions. This result is based on an abstract theorem proving the existence of finite eigenmeasures for some positive operators. We then consider a population with constant birth and death rates per individual and prove that there exists a unique quasi-stationary distribution with maximal exponential decay rate. The proof of uniqueness is based on an absolute continuity property with respect to a reference measure.     

A data mining framework for product and service migration analysis

With new technologies or products invented, customers migrate from a legacy product to a new product from time to time. This paper discusses a time series data mining framework for product and service migration analysis. In order to identify who migrate, how migrations look like, and the relationship between the legacy product and the new product, we first discuss certain characteristics of customer spending data associated with product migration. By exploring interesting patterns and defining a number of features that capture the associations between the spending time series, we develop a co-integration-based classifier to identify customers associated with migration and summarize their time series patterns before, during and after the migration. Customers can then be scored based on the migration index that integrates the statistical significance and business impact of migration customers. We illustrate the research through a case study of internet protocol (IP) migration in telecommunications and compare it with likelihood-ratio-based tests for change point detections.     

基于JGLM-RM模型的动态稳健设计及其应用

根据动态稳健设计的基本思想和方法,结合联合广义线性模型(Joint Generalized linearmodel)和响应模型(Response model)各自的特点和优势,构建出基于JGLM-RM的动态稳健设计模型。利用新模型对具体工业案例进行了实证研究,结果表明新模型不仅能有效地区分具体噪声因子和潜在噪声因子对整个过程波动的影响,而且能够灵活地调节模型的截距和斜率。此外,新模型引入了均值和散度的联合广义线性模型因此能适应广泛的响应类型。     

Detecting direct associations in a network by information theoretic approaches

Detecting direct associations or inferring networks based on the observed data is an important issue in many fields, including biology, physics, engineering and social studies. In this work, we focus on the information theoretic approaches in the network reconstruction or the direct association detection, in particular,for biological networks. We not only review the traditional approaches or measurements on the associations among the observed variables, such as correlation coefficient, mutual information and conditional mutual information(CMI), but also summarize recently developed theories and methods. The new theoretic works include:information geometry to give a unified framework in detecting causality/association, the partial independence to alleviate the singularity of CMI, and multiscale analysis of CMI to avoid the underestimation issue of CMI.The new methods include part mutual information(PMI) and partial associations(PA), which improve the old measurements in avoiding both overestimation and underestimation. All those theories and methods make important contributions as major advances in the development of network inference.     

Large exposure estimation through automatic business group identification

Large exposure rules are considered critical for financial institutions, as they directly restrict the lending activity of banks to clients. However, empirical evidence suggests that those rules are difficult both for regulators to enforce and for financial institutions to implement. We present a data-driven analytical model that automatically and algorithmically creates groups of related parties based on ownership information, financial dependencies, business associations, and family ties. We develop a methodology based on linear algebra and networks to group clients, highlight missing critical information, and identify unreported business partners. The approach can be used both prospectively by banking institutions analyzing credit risk and by regulators. We include a case study, applying the methodology retrospectively to highlight large exposure violations and systemic risk leading up to the 2008 banking crises in Iceland.     

A dynamical approach to logical decisions

We propose a first approximation to the modeling of cognitive decisions based on the theory of associative memories. The basic structure are the matrix memories of Anderson-Kohonen adapted to include the modulation of associations via tensorial preprocessing of inputs. This view admits an easy implementation of logical operations as matrix operators. From this “vectorial logic” springs a variety of models for fuzzy decision processes. Degrees of fuzziness are introduced at two different levels: (a) by the operators of modal logic, and (b) by using logical variables as vectors with projections inside the interval [0, 1]. The outcomes of this vectorial logic can be projected onto unit vectors yielding scalar difference equations. As examples we study the dynamics of contradictory self-referential systems and processes leading to competition between options. These models exhibit a variety of dynamical patterns that include stable steady states, oscillations, and deterministic chaos. © 1997 John Wiley & Sons, Inc.     

Assessing brand image through communalities and asymmetries in brand-to-attribute and attribute-to-brand associations

Brand image is a key component of customer-based brand equity, and refers to the associations a consumer holds in memory. Such associations are often directional; one should distinguish between brand-to-attribute and attribute-to-brand associations. Information on these associations arise from two ways of collecting data, respectively: brand-by-brand evaluations of all attributes and attribute-by-attributes evaluations of all brands. In this paper, the authors present a methodological approach, namely correspondence analysis of matched matrices, to assess the communalities as well as asymmetries between brand-to-attribute and attribute-to-brand associations. This allows studying whether or not there is match in a brand’s positioning (brand-to-attribute associations) and relative advantage (attribute-to-brand associations). The methodology results in perceptual maps visualizing brand image. The approach is illustrated in an empirical market research project in which two samples of consumers evaluated ten brands of deodorants and eleven attributes. The stability of the solution is examined using bootstrap resampling procedures.     

Assessment of numeracy in sports and exercise science students at an Australian university

The effect of high school study of mathematics on numeracy performance of sports and exercise science (SES) students is not clear. To investigate this further, we tested the numeracy skills of 401 students enrolled in a Bachelor of Health Sciences degree in SES using a multiple-choice survey consisting of four background questions and 39 numeracy test questions. Background questions (5-point scale) focused on highest level of mathematics studied at high school, self-perception of mathematics proficiency, perceived importance of mathematics to SES and likelihood of seeking help with mathematics. Numeracy questions focused on rational number, ratios and rates, basic algebra and graph interpretation. Numeracy performance was based on answers to these questions (1 mark each) and represented by the total score (maximum = 39). Students from first (n = 212), second (n = 78) and third (n = 111) years of the SES degree completed the test. The distribution of numeracy test scores for the entire cohort was negatively skewed with a median (IQR) score of 27(11). We observed statistically significant associations between test scores and the highest level of mathematics studied (P < 0.05), being lowest in students who studied Year 10 Mathematics (20 (9)), intermediate in students who studied Year 12 General Mathematics (26 (8)) and highest in two groups of students who studied higher-level Year 12 Mathematics (31 (9), 31 (6)). There were statistically significant associations between test scores and level of self-perception of mathematics proficiency and also likelihood of seeking help with mathematics (P < 0.05) but not with perceived importance of mathematics to SES. These findings reveal that the level of mathematics studied in high school is a critical factor determining the level of numeracy performance in SES students.     

Markov basis and Gröbner basis of Segre–Veronese configuration for testing independence in group-wise selections

We consider testing independence in group-wise selections with some restrictions on combinations of choices. We present models for frequency data of selections for which it is easy to perform conditional tests by Markov chain Monte Carlo (MCMC) methods. When the restrictions on the combinations can be described in terms of a Segre–Veronese configuration, an explicit form of a Gröbner basis consisting of binomials of degree two is readily available for performing a Markov chain. We illustrate our setting with the National Center Test for university entrance examinations in Japan. We also apply our method to testing independence hypotheses involving genotypes at more than one locus or haplotypes of alleles on the same chromosome.     

Organization and efficiency in the international insurance industry: A cross-frontier analysis

This paper employs cross-frontier analysis, an innovative tool based on data envelopment analysis, to provide new insight into the relationship between organization and efficiency in international insurance markets. We are the first to empirically test the expense preference hypothesis and the efficient structure hypothesis in a large cross-country study. For this purpose, we consider 23,807 firm-years for 21 countries from northern America and the European Union—a dataset not previously analyzed in this context. We find evidence for the efficient structure hypothesis in selected market segments, but we find no evidence for the expense preference hypothesis. Our results provide insight into the competitiveness of stock and mutual insurers from different countries. At the country level, the results can be used to compare different insurance markets. Our findings are especially interesting for the strategic management of insurance companies as well as for regulators and boards of national insurance associations.     

On the consensus protocol of conspecific agents

We present a class of consensus protocols over groups of agents with stochastically switching, directed, and weighted communication topologies. In this protocol, an agent’s traits, that is, the cardinality of its neighbor set and the weight assigned to its neighbors in the updating process, are given by two jointly distributed random variables and the neighbors of an agent are selected with equal probability. We provide closed form results for the asymptotic convergence rate and for the steady state mean square deviation in the presence of additive noise. These results are specialized to consensus protocols based on Erd?s–Rényi and numerosity-constrained networks.     

Efficient MIP formulation for optimal 1-for-N diversity coding

In the paper we consider a communication network that uses diversity coding in order to achieve reliability. Having a set of demands and a network topology we face a problem of optimal routing of the demands and backup trees, and associations between the demands and the backup trees. We present a compact mixed integer programming (MIP) formulation for the optimization problem, which proves to be more efficient than other approaches that can be found in the literature.     

MODEL SELECTION METHOD BASED ON MAXIMAL INFORMATION COEFFICIENT OF RESIDUALS

The traditional model selection criterions try to make a balance between fitted error and model complexity. Assumptions on the distribution of the response or the noise, which may be misspecified, should be made before using the traditional ones. In this ar- ticle, we give a new model selection criterion, based on the assumption that noise term in the model is independent with explanatory variables, of minimizing the association strength between regression residuals and the response, with fewer assumptions. Maximal Information Coe~cient （MIC）, a recently proposed dependence measure, captures a wide range of associ- ations, and gives almost the same score to different type of relationships with equal noise, so MIC is used to measure the association strength. Furthermore, partial maximal information coefficient （PMIC） is introduced to capture the association between two variables removing a third controlling random variable. In addition, the definition of general partial relationship is given.     

Model selection method based on maximal information coefficient of residuals

The traditional model selection criterions try to make a balance between fitted error and model complexity. Assumptions on the distribution of the response or the noise, which may be misspecified, should be made before using the traditional ones. In this article, we give a new model selection criterion, based on the assumption that noise term in the model is independent with explanatory variables, of minimizing the association strength between regression residuals and the response, with fewer assumptions. Maximal Information Coefficient (MIC), a recently proposed dependence measure, captures a wide range of associations, and gives almost the same score to different type of relationships with equal noise, so MIC is used to measure the association strength. Furthermore, partial maximal information coefficient (PMIC) is introduced to capture the association between two variables removing a third controlling random variable. In addition, the definition of general partial relationship is given.