More efficient estimators for marginal additive hazards model in case-cohort studies with multiple outcomes

Case-cohort study designs are widely used to reduce the cost of large cohort studies. When several diseases are of interest, we can use the same subcohort. In this paper, we will study the casecohort design of marginal additive hazards model for multiple outcomes by a more efficient version. Instead of analyzing each disease separately, ignoring the additional exposure measurements collected on subjects with other diseases, we propose a new weighted estimating equation approach to improve the efficiency by utilizing as much information collected as possible. The consistency and asymptotic normality of the resulting estimator are established. Simulation studies are conducted to examine the finite sample performance of the proposed estimator, which confirm the efficiency gains.     

ToF‐SIMS analysis of a polymer microarray composed of poly(meth)acrylates with C6 derivative pendant groups

Surface analysis plays a key role in understanding the function of materials, particularly in biological environments. Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) provides highly surface sensitive chemical information that can readily be acquired over large areas and has, thus, become an important surface analysis tool. However, the information‐rich nature of ToF‐SIMS complicates the interpretation and comparison of spectra, particularly in cases where multicomponent samples are being assessed. In this study, a method is presented to assess the chemical variance across 16 poly(meth)acrylates. Materials are selected to contain C₆ pendant groups, and ten replicates of each are printed as a polymer microarray. SIMS spectra are acquired for each material with the most intense and unique ions assessed for each material to identify the predominant and distinctive fragmentation pathways within the materials studied. Differentiating acrylate/methacrylate pairs is readily achieved using secondary ions derived from both the polymer backbone and pendant groups. Principal component analysis (PCA) is performed on the SIMS spectra of the 16 polymers, whereby the resulting principal components are able to distinguish phenyl from benzyl groups, mono‐functional from multi‐functional monomers and acrylates from methacrylates. The principal components are applied to copolymer series to assess the predictive capabilities of the PCA. Beyond being able to predict the copolymer ratio, in some cases, the SIMS analysis is able to provide insight into the molecular sequence of a copolymer. The insight gained in this study will be beneficial for developing structure–function relationships based upon ToF‐SIMS data of polymer libraries. © 2016 The Authors Surface and Interface Analysis Published by John Wiley & Sons Ltd.     

聚集数据多元线性模型参数的多元聚集综合岭估计的相对效率

对于聚集数据的多元线性模型,提出了参数的多元聚集综合岭估计的概念,给出了多元聚集综合岭估计相对于最小二乘估计及最佳线性无偏估计的两种相对效率,并得到了这两种相对效率的上界.应用Monte Carlo模拟,验证了有关结论是合理的.     

单纯型上Meyer-K(o)nig-Zeller算子逼近收敛阶的估计

利用分解技巧及一元的结论,讨论单纯型上Meyer-K(o)nig-Zeller算子逼近的收敛阶,得到逼近的正定理.     

Utilizing AgNPt-SALDI to Classify Edible Oils by Multivariate Statistics of Triacylglycerol Profile

Edible oils are valuable sources of nutrients, and their classification is necessary to ensure high quality, which is essential to food safety. This study reports the establishment of a rapid and straightforward SALDI-TOF MS platform used to detect triacylglycerol (TAG) in various edible oils. Silver nanoplates (AgNPts) were used to optimize the SALDI samples for high sensitivity and reproducibility of TAG signals. TAG fingerprints were combined with multivariate statistics to identify the critical features of edible oil discrimination. Eleven various edible oils were discriminated using principal component analysis (PCA). The results suggested the creation of a robust platform that can examine food adulteration and food fraud, potentially ensuring high-quality foods and agricultural products.     

多元方差分析在蚕桑方面的应用

本文应用多元方差分析对不同的桑品种、蚕品种的养蚕成绩（全茧量、茧层量）及制种成绩（造卵数、产卵数）进行分析,得到多倍体桑的制种成绩极显著地高于二倍体桑;三倍体桑饲养的苏５蚕品种的养蚕成绩为最佳的结论,为养蚕、制种生产提供了一定的理论依据     

Uniform designs for mixture-amount experiments and for mixture experiments under order restrictions

With order statistics of the uniform distribution on [0, l], exponential and beta distributions, a stochastic representation is obtained for the uniform distribution over various domains, where A-type domains are closely associated with reliability growth analysis, order restricted statistical inference and isotonic regression theory, V-type domains are connected with the mixture-amount experiments, and T-type domains are well related to mixture experiments. With these stochastic representations, the corresponding uniform distribution and number-theoretic nets can be generated. This approach seems to be new and is called order statistics method. Some examples on reliability growth analysis and experimental design are presented. This work was partially supported by a Hong Kong UGC-RGC grant, the Statistics Research and Consultancy Centre of HK-BU, and the Chinese Academy of Sciences.     

Moment Estimation for Multivariate Extreme Value Distribution in a Nested Logistic Model

This paper considers multivariate extreme value distribution in a nested logistic model. The dependence structure for this model is discussed. We find a useful transformation that transformed variables possess the mixed independence. Thus, the explicit algebraic formulae for a characteristic function and moments may be given. We use the method of moments to derive estimators of the dependence parameters and investigate the properties of these estimators in large samples via asymptotic theory and in finite samples via computer simulation. We also compare moment estimation with a maximum likelihood estimation in finite sample sizes. The results indicate that moment estimation is good for all practical purposes.     

Strictly positive definite functions on the complex Hilbert sphere

We study strictly positive definite functions on the complex Hilbert sphere. A link between strict positive definiteness and (harmonic) polynomial interpolation on finite‐dimensional spheres is investigated. Sufficient conditions for strict positive definiteness are presented. This revised version was published online in June 2006 with corrections to the Cover Date.     

Near-infrared (NIR) spectroscopic evaluation of articular cartilage: A review of current and future trends

This review describes recent developments and applications of near-infrared (NIR) spectroscopy for characterization of articular cartilage integrity. It summarizes the research findings in this area and presents some spectral ranges and peaks associated with the different properties and components of articular cartilage. We further describe recent adaptations of NIR spectroscopy for clinical evaluation of articular cartilage injury and degeneration. Critical to accurate decision-making during repair surgery is having clear knowledge of lesion severity and spread, and how to grade the quality of surrounding cartilage. Thus, in this review, we detail efforts aimed at quantification and classification of cartilage pathology using NIR spectroscopy. Finally, we present open questions and challenges with a view to guiding future directions in NIR spectroscopy research on articular cartilage.