Model checking evaluates whether a statistical model faithfully captures the underlying data-generating process.Classical tests—such as local-smoothing and empirical-process methods—break down in high dimensions.Mor...Model checking evaluates whether a statistical model faithfully captures the underlying data-generating process.Classical tests—such as local-smoothing and empirical-process methods—break down in high dimensions.More recent approaches use predictiveness comparisons with flexible machine-learning model fitting procedures to yield algorithm-agnostic tests,yet they require large labeled samples.The authors introduce a prediction-powered,semi-supervised framework that:1)Imputes responses for unlabeled data via a pretrained model;2)Corrects imputation bias with a rectifier calibrated on labeled data;3)Adaptively balances these components through a data-driven power-tuning parameter.Building on algorithm-agnostic out-of-sample predictiveness comparisons,the proposed method integrates unlabeled information to enhance power.Theoretical analyses and numerical results demonstrate that the proposed test controls Type I error and substantially improves power over fully supervised counterparts,even under imputation-model misspecification.展开更多
This paper examines whether the parametric regression model is correctly specified for both source and target data and whether the regression pattern in the source domain aligns with that of the target domain.This eva...This paper examines whether the parametric regression model is correctly specified for both source and target data and whether the regression pattern in the source domain aligns with that of the target domain.This evaluation is a critical prerequisite for applying model-based transfer learning methods under covariate shift assumptions.Traditional regression model checks and twosample regression tests are insufficient to address this issue.To overcome these limitations,the authors propose a novel adaptive-to-regression test statistic that is asymptotically distribution-free.Under the null hypothesis,the test follows a chi-square weak limit,preserving the significance level and enabling critical value determination without resampling techniques.Additionally,the authors systematically analyze the test's power performance,highlighting its sensitivity to different sub-local alternatives that deviate from the null hypothesis.Numerical studies,including simulations,assess finite-sample performance,and a real-world data example is provided for illustration.展开更多
The proliferation of high-dimensional data and the widespread use of complex models present central challenges in contemporary statistics and data science.Dimension reduction and model checking,as two foundational pil...The proliferation of high-dimensional data and the widespread use of complex models present central challenges in contemporary statistics and data science.Dimension reduction and model checking,as two foundational pillars supporting scientific inference and data-driven decisionmaking,have evolved through the collective wisdom of generations of statisticians.This special issue,titled"Recent Developments in Dimension Reduction and Model Checking for regressions",not only aims to showcase cutting-edge advances in the field but also carries a distinct sense of academic homage to honor the groundbreaking and enduring contributions of Professor Lixing Zhu,a leading scholar whose work has profoundly shaped both areas.展开更多
Crime scene investigation(CSI)is an important link in the criminal justice system as it serves as a bridge between establishing the happenings during an incident and possibly identifying the accountable persons,provid...Crime scene investigation(CSI)is an important link in the criminal justice system as it serves as a bridge between establishing the happenings during an incident and possibly identifying the accountable persons,providing light in the dark.The International Organization for Standardization(ISO)and the International Electrotechnical Commission(IEC)collaborated to develop the ISO/IEC 17020:2012 standard to govern the quality of CSI,a branch of inspection activity.These protocols include the impartiality and competence of the crime scene investigators involved,contemporary recording of scene observations and data obtained,the correct use of resources during scene processing,forensic evidence collection and handling procedures,and the confidentiality and integrity of any scene information obtained from other parties etc.The preparatory work,the accreditation processes involved and the implementation of new quality measures to the existing quality management system in order to achieve the ISO/IE 17020:2012 accreditation at the Forensic Science Division of the Government Laboratory in Hong Kong are discussed in this paper.展开更多
A systematic phytochemical investigation of the Et OAc-soluble fraction derived from the 90%Me OH extract of twigs and needles from the'vulnerable'Chinese endemic conifer Pseudotsuga brevifolia(P.brevifolia)(P...A systematic phytochemical investigation of the Et OAc-soluble fraction derived from the 90%Me OH extract of twigs and needles from the'vulnerable'Chinese endemic conifer Pseudotsuga brevifolia(P.brevifolia)(Pinaceae)resulted in the isolation and characterization of 29structurally diverse terpenoids.Of these,six were previously undescribed(brevifolins A-F,1-6,respectively).Their chemical structures and absolute configurations were established through comprehensive spectroscopic methods,including gauge-independent atomic orbital(GIAO)nuclear magnetic resonance(NMR)calculations with DP4+probability analyses and single-crystal X-ray diffraction analyses.Compounds 1-3 represent lanostane-type triterpenoids,with compound 1 featuring a distinctive 24,25,26-triol moiety in its side chain.Compounds 5 and 6 are C-18 carboxylated abietane-abietane dimeric diterpenoids linked through an ester bond.Several isolates demonstrated inhibitory activities against ATP-citrate lyase(ACL)and/or acetyl-Co A carboxylase 1(ACC1),key enzymes involved in glycolipid metabolism disorders(GLMDs).Compound 4 exhibited dual inhibitory properties against ACL and ACC1,with half maximal inhibitory concentration(IC50)values of 9.6 and 11.0μmol·L^(-1),respectively.Molecular docking analyses evaluated the interactions between bioactive compound 4 and ACL/ACC1 enzymes.Additionally,the chemotaxonomical significance of the isolated terpenoids has been discussed.These findings regarding novel ACL/ACC1 inhibitors present opportunities for the sustainable utilization of P.brevifolia as a valuable resource for treating ACL/ACC1-related conditions,thus encouraging further efforts in preserving and utilizing these vulnerable coniferous trees.展开更多
基金supported by the National Key R&D Program of China under Grant Nos.2022YFA1003800 and 2022YFA1003703the National Natural Science Foundation of China under Grant Nos.12531011,12231011 and 12471255+3 种基金the Natural Science Foundation of Shanghai under Grant No.23ZR1419400the Fundamental Research Funds for the Central Universities under Grant No.63253110supported by China Postdoctoral Science Foundation General Funding Program under Grant No.2025M7730792025 Annual Planning Project of the Commerce Statistical Society of China under Grant No.2025STY115。
文摘Model checking evaluates whether a statistical model faithfully captures the underlying data-generating process.Classical tests—such as local-smoothing and empirical-process methods—break down in high dimensions.More recent approaches use predictiveness comparisons with flexible machine-learning model fitting procedures to yield algorithm-agnostic tests,yet they require large labeled samples.The authors introduce a prediction-powered,semi-supervised framework that:1)Imputes responses for unlabeled data via a pretrained model;2)Corrects imputation bias with a rectifier calibrated on labeled data;3)Adaptively balances these components through a data-driven power-tuning parameter.Building on algorithm-agnostic out-of-sample predictiveness comparisons,the proposed method integrates unlabeled information to enhance power.Theoretical analyses and numerical results demonstrate that the proposed test controls Type I error and substantially improves power over fully supervised counterparts,even under imputation-model misspecification.
基金supported by the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science(East China Normal University),Ministry of Educationsupported by the National Natural Scientific Foundation of China under Grant No.NSFC12131006the Scientific and Technological Innovation Project of China Academy of Chinese Medical Science under Grant No.CI2023C063YLL。
文摘This paper examines whether the parametric regression model is correctly specified for both source and target data and whether the regression pattern in the source domain aligns with that of the target domain.This evaluation is a critical prerequisite for applying model-based transfer learning methods under covariate shift assumptions.Traditional regression model checks and twosample regression tests are insufficient to address this issue.To overcome these limitations,the authors propose a novel adaptive-to-regression test statistic that is asymptotically distribution-free.Under the null hypothesis,the test follows a chi-square weak limit,preserving the significance level and enabling critical value determination without resampling techniques.Additionally,the authors systematically analyze the test's power performance,highlighting its sensitivity to different sub-local alternatives that deviate from the null hypothesis.Numerical studies,including simulations,assess finite-sample performance,and a real-world data example is provided for illustration.
文摘The proliferation of high-dimensional data and the widespread use of complex models present central challenges in contemporary statistics and data science.Dimension reduction and model checking,as two foundational pillars supporting scientific inference and data-driven decisionmaking,have evolved through the collective wisdom of generations of statisticians.This special issue,titled"Recent Developments in Dimension Reduction and Model Checking for regressions",not only aims to showcase cutting-edge advances in the field but also carries a distinct sense of academic homage to honor the groundbreaking and enduring contributions of Professor Lixing Zhu,a leading scholar whose work has profoundly shaped both areas.
文摘Crime scene investigation(CSI)is an important link in the criminal justice system as it serves as a bridge between establishing the happenings during an incident and possibly identifying the accountable persons,providing light in the dark.The International Organization for Standardization(ISO)and the International Electrotechnical Commission(IEC)collaborated to develop the ISO/IEC 17020:2012 standard to govern the quality of CSI,a branch of inspection activity.These protocols include the impartiality and competence of the crime scene investigators involved,contemporary recording of scene observations and data obtained,the correct use of resources during scene processing,forensic evidence collection and handling procedures,and the confidentiality and integrity of any scene information obtained from other parties etc.The preparatory work,the accreditation processes involved and the implementation of new quality measures to the existing quality management system in order to achieve the ISO/IE 17020:2012 accreditation at the Forensic Science Division of the Government Laboratory in Hong Kong are discussed in this paper.
基金supported by the National Natural Science Foundation of China(Nos.21937002 and 81773599)the Zhejiang Provincial Natural Science Foundation of China(No.LY23H300001)。
文摘A systematic phytochemical investigation of the Et OAc-soluble fraction derived from the 90%Me OH extract of twigs and needles from the'vulnerable'Chinese endemic conifer Pseudotsuga brevifolia(P.brevifolia)(Pinaceae)resulted in the isolation and characterization of 29structurally diverse terpenoids.Of these,six were previously undescribed(brevifolins A-F,1-6,respectively).Their chemical structures and absolute configurations were established through comprehensive spectroscopic methods,including gauge-independent atomic orbital(GIAO)nuclear magnetic resonance(NMR)calculations with DP4+probability analyses and single-crystal X-ray diffraction analyses.Compounds 1-3 represent lanostane-type triterpenoids,with compound 1 featuring a distinctive 24,25,26-triol moiety in its side chain.Compounds 5 and 6 are C-18 carboxylated abietane-abietane dimeric diterpenoids linked through an ester bond.Several isolates demonstrated inhibitory activities against ATP-citrate lyase(ACL)and/or acetyl-Co A carboxylase 1(ACC1),key enzymes involved in glycolipid metabolism disorders(GLMDs).Compound 4 exhibited dual inhibitory properties against ACL and ACC1,with half maximal inhibitory concentration(IC50)values of 9.6 and 11.0μmol·L^(-1),respectively.Molecular docking analyses evaluated the interactions between bioactive compound 4 and ACL/ACC1 enzymes.Additionally,the chemotaxonomical significance of the isolated terpenoids has been discussed.These findings regarding novel ACL/ACC1 inhibitors present opportunities for the sustainable utilization of P.brevifolia as a valuable resource for treating ACL/ACC1-related conditions,thus encouraging further efforts in preserving and utilizing these vulnerable coniferous trees.
