A class of pseudo distances is used to derive test statistics using transformed data or spacings for testing goodness-of-fit for parametric models. These statistics can be considered as density based statistics and ex...A class of pseudo distances is used to derive test statistics using transformed data or spacings for testing goodness-of-fit for parametric models. These statistics can be considered as density based statistics and expressible as simple functions of spacings. It is known that when the null hypothesis is simple, the statistics follow asymptotic normal distributions without unknown parameters. In this paper we emphasize results for the null composite hypothesis: the parameters can be estimated by a generalized spacing method (GSP) first which is equivalent to minimize a pseudo distance from the class which is considered;subsequently the estimated parameters are used to replace the parameters in the pseudo distance used for estimation;goodness-of-fit statistics for the composite hypothesis can be constructed and shown to have again an asymptotic normal distribution without unknown parameters. Since these statistics are related to a discrepancy measure, these tests can be shown to be consistent in general. Furthermore, due to the simplicity of these statistics and they come a no extra cost after fitting the model, they can be considered as alternative statistics to chi-square statistics which require a choice of intervals and statistics based on empirical distribution (EDF) using the original data with a complicated null distribution which might depend on the parametric family being considered and also might depend on the vector of true parameters but EDF tests might be more powerful against some specific models which are specified by the alternative hypothesis.展开更多
Objective:Understanding how brain changes over lifetime provides the basis for new insights into neurophysiology and neuropathology.In this study,we carried out a pseudo-longitudinal study based on age-related Chinese...Objective:Understanding how brain changes over lifetime provides the basis for new insights into neurophysiology and neuropathology.In this study,we carried out a pseudo-longitudinal study based on age-related Chinese brain atlases(i.e.,Chinese2020)constructed from large-scale volumetric brain MRI data collected in normal Han Chinese adults at varying ages.Methods:In order to quantify the deformation and displacement of brains for each voxel as age increases,optical flow algorithm was employed to compute motion vectors between every two consecutive brain templates of the age-related brain atlas,i.e.,Chinese2020.Results:Dynamic age-related neuroanatomical changes in a standardized brain space were shown.Overall,our results demonstrate that brain inward deformation(mainly due to atrophy)can appear in adulthood and this trend generally accelerates as age increases,affecting multiple regions including frontal cortex,temporal cortex,parietal cortex,and cerebellum,whereas occipital cortex is least affected by aging,and even showed some degree of outward deformation in the midlife.Conclusion:Our findings indicated more complicated age-related changes instead of a simple trend of brain volume decrease,which may be in line with the recently increasing interests in the age-related cortical complexity with other morphometry measures.展开更多
为提高冷热电联供(Combined Cooling Heating and Power,CCHP)型微网的综合运行效益,建立了以运行费用最小和二氧化碳排放量最小为目标的优化模型。针对源荷的不确定性,提出了基于误差场景整体生成与缩减的典型场景获得方法,并引入伪F-...为提高冷热电联供(Combined Cooling Heating and Power,CCHP)型微网的综合运行效益,建立了以运行费用最小和二氧化碳排放量最小为目标的优化模型。针对源荷的不确定性,提出了基于误差场景整体生成与缩减的典型场景获得方法,并引入伪F-统计(Pseudo F-statistics,PFS)指标用于确定最佳场景缩减数目。实例计算表明,与不考虑源荷不确定的确定性优化方法相比,所提方法在应对源荷的不确定性上具有较好效果,运行费用平均下降0.31%,二氧化碳排放量平均下降4.85%。此外,计算分析表明,应用PFS指标确定最佳聚类数目可以找到模型应对源荷不确定的能力与计算时间之间的平衡点,提高模型计算效率。展开更多
文摘A class of pseudo distances is used to derive test statistics using transformed data or spacings for testing goodness-of-fit for parametric models. These statistics can be considered as density based statistics and expressible as simple functions of spacings. It is known that when the null hypothesis is simple, the statistics follow asymptotic normal distributions without unknown parameters. In this paper we emphasize results for the null composite hypothesis: the parameters can be estimated by a generalized spacing method (GSP) first which is equivalent to minimize a pseudo distance from the class which is considered;subsequently the estimated parameters are used to replace the parameters in the pseudo distance used for estimation;goodness-of-fit statistics for the composite hypothesis can be constructed and shown to have again an asymptotic normal distribution without unknown parameters. Since these statistics are related to a discrepancy measure, these tests can be shown to be consistent in general. Furthermore, due to the simplicity of these statistics and they come a no extra cost after fitting the model, they can be considered as alternative statistics to chi-square statistics which require a choice of intervals and statistics based on empirical distribution (EDF) using the original data with a complicated null distribution which might depend on the parametric family being considered and also might depend on the vector of true parameters but EDF tests might be more powerful against some specific models which are specified by the alternative hypothesis.
基金supported by grants from the Innovation and Technology Commission(Project Nos.GHP-025-17SZ and GHP/028/14SZ)of the Hong Kong Special Administrative RegionShenzhen Science and Technology Innovation Committee(Project NoCYZZ20160421160735632)+2 种基金Beijing Nova Program(No.2016000021223TD07)Capacity Building for Sci-Tech Innovation￡-Fundamental Scientific Research Funds(No.19530050157,No.19530050184)the Beijing Brain Initiative of Beijing Municipal Science&Technology Commission.
文摘Objective:Understanding how brain changes over lifetime provides the basis for new insights into neurophysiology and neuropathology.In this study,we carried out a pseudo-longitudinal study based on age-related Chinese brain atlases(i.e.,Chinese2020)constructed from large-scale volumetric brain MRI data collected in normal Han Chinese adults at varying ages.Methods:In order to quantify the deformation and displacement of brains for each voxel as age increases,optical flow algorithm was employed to compute motion vectors between every two consecutive brain templates of the age-related brain atlas,i.e.,Chinese2020.Results:Dynamic age-related neuroanatomical changes in a standardized brain space were shown.Overall,our results demonstrate that brain inward deformation(mainly due to atrophy)can appear in adulthood and this trend generally accelerates as age increases,affecting multiple regions including frontal cortex,temporal cortex,parietal cortex,and cerebellum,whereas occipital cortex is least affected by aging,and even showed some degree of outward deformation in the midlife.Conclusion:Our findings indicated more complicated age-related changes instead of a simple trend of brain volume decrease,which may be in line with the recently increasing interests in the age-related cortical complexity with other morphometry measures.
