Visualization for Large‐scale Gaussian Updates

In geostatistics and also in other applications in science and engineering, it is now common to perform updates on Gaussian process models with many thousands or even millions of components. These large‐scale inferences involve modelling, representational and computational challenges. We describe a visualization tool for large‐scale Gaussian updates, the ‘medal plot’. The medal plot shows the updated uncertainty at each observation location and also summarizes the sharing of information across observations, as a proxy for the sharing of information across the state vector (or latent process). As such, it reflects characteristics of both the observations and the statistical model. We illustrate with an application to assess mass trends in the Antarctic Ice Sheet, for which there are strong constraints from the observations and the physics.     

A search of maximum generalized resolution quaternary-code designs via integer linear programming

Quaternary-code (QC) designs, an attractive class of nonregular fractional factorial designs, have received much attention due to their theoretical elegance and practical applicability. Some recent works of QC designs revealed their good properties over their regular counterparts under commonly used criteria. We develop an optimization tool that can maximize the generalized resolution of a QC design of a given size. The problem can be recast as an integer linear programming (ILP) problem through a linear simplification that combines the \(k\)- and \(a\)-equations, even though the generalized resolution does not linearly depend on the aliasing indexes. The ILP surprisingly improves a class of \((1/16)\)th-fraction QC designs with higher generalized resolutions. It also applies to obtain some \((1/64)\)th-fraction QC designs with maximum generalized resolutions, and these QC designs generally have higher generalized resolutions than the regular designs of the same size.     

Goodness-of-fit tests of generalized linear mixed models for repeated ordinal responses

Categorical longitudinal data are frequently applied in a variety of fields, and are commonly fitted by generalized linear mixed models (GLMMs) and generalized estimating equations models. The cumulative logit is one of the useful link functions to deal with the problem involving repeated ordinal responses. To check the adequacy of the GLMMs with cumulative logit link function, two goodness-of-fit tests constructed by the unweighted sum of squared model residuals using numerical integration and bootstrap resampling technique are proposed. The empirical type I error rates and powers of the proposed tests are examined by simulation studies. The ordinal longitudinal studies are utilized to illustrate the application of the two proposed tests.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.     

Functional Partial Linear Single‐index Model

This paper deals with the problem of predicting the real‐valued response variable using explanatory variables containing both multivariate random variable and random curve. The proposed functional partial linear single‐index model treats the multivariate random variable as linear part and the random curve as functional single‐index part, respectively. To estimate the non‐parametric link function, the functional single‐index and the parameters in the linear part, a two‐stage estimation procedure is proposed. Compared with existing semi‐parametric methods, the proposed approach requires no initial estimation and iteration. Asymptotical properties are established for both the parameters in the linear part and the functional single‐index. The convergence rate for the non‐parametric link function is also given. In addition, asymptotical normality of the error variance is obtained that facilitates the construction of confidence region and hypothesis testing for the unknown parameter. Numerical experiments including simulation studies and a real‐data analysis are conducted to evaluate the empirical performance of the proposed method.     

电动空调涡旋压缩机型线优化

选取我国三大经济区2001—2017年的数据,运用面板数据模型分析了政府财政、金融市场及其相互作用对区域自主创新能力提升的影响,结果表明:政府财政对自主创新能力的提升作用较金融市场更为显著,但三大经济区存在差异;就全国总体而言,金融支持效率指标在是否存在政府中介的情况下均不显著,金融市场对自主创新的支持效率还很低下;误差修正模型表明区域自主创新能力提升还受自身前期自主创新能力水平影响;人力资本的投入对区域自主创新能力的提升起到至关重要的作用。     

城市化进程中少数民族流动人口就业现状、存在问题及其对策分析

城市化进程的加快,必然导致人口流动,更多少数民族人口流动到城市就业.作者对成都市少数民族流动人口就业现状、特征进行了调查,分析了少数民族流动人口就业存在的问题,并就与之相关的对策进行了探讨.     

农民工生存现状与和谐城市构建

城市化进程中的民工潮是中国由传统农业社会向现代工业社会过渡的大势所趋。随着城镇二三产业发展加快,农民工进入城市的人数逐渐增多,已经事实上成为城市建设者和生存者的一员（社会阶层）。但在城市GDP大幅增长的同时,农民工与城镇居民在现实生活方面的差距却越来越大,已经严重地影响到社会的稳定发展。当前,农民工的生存、发展同题应当引起各级政府部门的高度重视。只有真正做到农民工在政治权益、经济待遇上的公平、公正,才能保证社会的和谐发展。     

软件技术专业的课程体系与职业能力培养

就软件技术专业课程体系的教学改革实践,从培养目标、教学模式、教学内容、课程设置以及师资培养等方面的改革思想进行了阐述。     

商品房中环境经济价值的评估研究及其应用

如何对商品房中环境的经济价值进行评估?目前国内还缺乏系统性和可操作性较强的评估体系。本文尝试建立了一套全面衡量居住房产价值的评估指标体系。应用该体系对市场调查统计结果的分析表明:目前商品房总价值与"非环境因素"相关性较大,而"环境因素"占其价值的比例随着房价增高而增加。该体系的应用有助于提高市场的透明度,兼顾房地产经济的公平与效率,且有利于房地产经济的发展与环境保护的相互促进。