The concept of cointegration is widely used in applied non-stationary time series analysis to describe the co-movement of data measured over time. In this paper, we proposed a Bayesian model for cointegration test and...The concept of cointegration is widely used in applied non-stationary time series analysis to describe the co-movement of data measured over time. In this paper, we proposed a Bayesian model for cointegration test and analysis, based on the dynamic latent factor framework. Efficient computational algorithms are also developed based on Markov Chain Monte Carlo (MCMC). Performance and efficiency of the the model and approaches are assessed by simulated and real data analysis.展开更多
To solve the problem of the spatial correlation for adjacent areas in traditional spectral unmixing methods, we propose an area-correlated spectral unmixing method based on Bayesian nonnegative matrix factorization. I...To solve the problem of the spatial correlation for adjacent areas in traditional spectral unmixing methods, we propose an area-correlated spectral unmixing method based on Bayesian nonnegative matrix factorization. In the proposed me-thod, the spatial correlation property between two adjacent areas is expressed by a priori probability density function, and the endmembers extracted from one of the adjacent areas are used to estimate the priori probability density func-tions of the endmembers in the current area, which works as a type of constraint in the iterative spectral unmixing process. Experimental results demonstrate the effectivity and efficiency of the proposed method both for synthetic and real hyperspectral images, and it can provide a useful tool for spatial correlation and comparation analysis between ad-jacent or similar areas.展开更多
A Bayesian network (BN) model was developed to predict susceptibility to PWD(Pine Wilt Disease). The distribution of PWD was identified using QuickBird and unmanned aerial vehicle (UAV) images taken at different times...A Bayesian network (BN) model was developed to predict susceptibility to PWD(Pine Wilt Disease). The distribution of PWD was identified using QuickBird and unmanned aerial vehicle (UAV) images taken at different times. Seven factors that influence the distribution of PWD were extracted from the QuickBird images and were used as the independent variables. The results showed that the BN model predicted PWD with high accuracy. In a sensitivity analysis, elevation (EL), the normal differential vegetation index (NDVI), the distance to settlements (DS) and the distance to roads (DR) were strongly associated with PWD prevalence, and slope (SL) exhibited the weakest association with PWD prevalence. The study showed that BN is an effective tool for modeling PWD prevalence and quantifying the impact of various factors.展开更多
目的探讨海南省肺结核发病的时空特征及其相关因素,为制定海南省肺结核防控策略提供参考依据。方法整合2014—2023年海南各市县肺结核报告病例、气象、社会经济和卫生资源资料,构建5个层次递进的贝叶斯时空模型,逐步引入时空效应,采用...目的探讨海南省肺结核发病的时空特征及其相关因素,为制定海南省肺结核防控策略提供参考依据。方法整合2014—2023年海南各市县肺结核报告病例、气象、社会经济和卫生资源资料,构建5个层次递进的贝叶斯时空模型,逐步引入时空效应,采用集成嵌套拉普拉斯逼近(integrated nested Laplace approximation,INLA)算法进行贝叶斯推断,并依据偏差信息准则(deviance information criterion,DIC)、渡边赤池信息准则(Watanabe-Akaike information criterion,WAIC)和条件预测纵坐标(conditional predictive ordinates,CPO)选择最优模型,对肺结核发病的时空特征及影响因素进行分析。结果2014—2023年海南省各市县结核病发病风险存在空间异质性,模型估计的相对风险值范围为0.840~1.580,发病相对风险整体呈现东南沿海最高、西部次之、北部及中南部普遍较低的分布特征。2014—2023年发病年度相对风险围绕基准线低幅振荡,范围为0.968~1.029;月度相对风险则呈现季节特征,在1月和3月达到冬春季高峰,而在夏季的8、9月以及12月则降至基准以下。时空交互效应分析显示,全省肺结核发病风险整体呈下降趋势,区域间风险差异缩小。影响因素分析显示,气温(RR=0.988,95%CI:0.978~0.997)与气压(RR=0.994,95%CI:0.991~0.998)为保护因素,日照时数(RR=1.002,95%CI:1.001~1.003)是危险因素,农村人均纯收入为有统计学意义的保护因素,但其效应量极小。结论海南省肺结核发病呈现明显的时空异质性,受气象和社会经济因素影响。建议实施差异化防控,建立气象响应机制,并在发病高峰季节加强干预,同时巩固农村防控基础,以发挥保护作用。展开更多
目的评估1990~2021年中国归因于生活方式和代谢因素缺血性脑卒中(ischemic stroke,IS)的疾病负担,并预测未来20年IS的疾病负担。方法收集全球疾病负担(global burden of disease,GBD)2021数据库中归因于生活方式和代谢因素的IS不同性别...目的评估1990~2021年中国归因于生活方式和代谢因素缺血性脑卒中(ischemic stroke,IS)的疾病负担,并预测未来20年IS的疾病负担。方法收集全球疾病负担(global burden of disease,GBD)2021数据库中归因于生活方式和代谢因素的IS不同性别、年龄的死亡率、伤残调整寿命年(disability adjusted life years,DALY)率、年龄标准化死亡率(age-standardized mortality rate,ASMR)和年龄标准化伤残调整寿命年率(age-standardized rate of disability adjusted life years,ASDR)。使用Joinpoint回归分析IS的ASMR和ASDR的年度变化率和平均年度变化率。使用贝叶斯年龄-时期-队列(Bayesian age-period-cohort,BAPC)模型预测未来20年IS的ASMR和ASDR发展趋势。结果中国2021年归因于饮食风险、高空腹血糖、高低密度脂蛋白胆固醇(low-density lipoprotein cholesterol,LDL-C)、低体力劳动、烟草的IS的ASMR和ASDR均低于1990年,归因于高体质量指数(body mass index,BMI)的ASMR和ASDR高于1990年,归因于高收缩压的IS疾病负担最重。1990~2021年我国女性归因于高LDL-C和低体力活动的IS的ASMR和ASDR呈下降趋势,男性未见明显变化;男性归因于高收缩压的IS的ASMR和ASDR呈上升趋势,女性呈下降趋势;男性和女性归因于高BMI的IS的ASMR和ASDR呈上升趋势,男性IS的疾病负担要高于女性。我国IS的疾病负担随着年龄的增大而增加。未来20年我国归因于饮食风险、高收缩压、高空腹血糖、高LDL-C、低体力劳动、烟草的IS疾病负担逐步降低,归因于高BMI的IS疾病负担逐步上升。结论中国归因于饮食风险、高空腹血糖、高LDL-C、低体力劳动、烟草的IS疾病负担虽然持续呈下降趋势,但是IS的防治形式依旧严峻,归因于高BMI的IS疾病负担呈持续上升趋势,未来需针对重点人群(高龄、男性等)精准施策。展开更多
文摘The concept of cointegration is widely used in applied non-stationary time series analysis to describe the co-movement of data measured over time. In this paper, we proposed a Bayesian model for cointegration test and analysis, based on the dynamic latent factor framework. Efficient computational algorithms are also developed based on Markov Chain Monte Carlo (MCMC). Performance and efficiency of the the model and approaches are assessed by simulated and real data analysis.
文摘To solve the problem of the spatial correlation for adjacent areas in traditional spectral unmixing methods, we propose an area-correlated spectral unmixing method based on Bayesian nonnegative matrix factorization. In the proposed me-thod, the spatial correlation property between two adjacent areas is expressed by a priori probability density function, and the endmembers extracted from one of the adjacent areas are used to estimate the priori probability density func-tions of the endmembers in the current area, which works as a type of constraint in the iterative spectral unmixing process. Experimental results demonstrate the effectivity and efficiency of the proposed method both for synthetic and real hyperspectral images, and it can provide a useful tool for spatial correlation and comparation analysis between ad-jacent or similar areas.
文摘A Bayesian network (BN) model was developed to predict susceptibility to PWD(Pine Wilt Disease). The distribution of PWD was identified using QuickBird and unmanned aerial vehicle (UAV) images taken at different times. Seven factors that influence the distribution of PWD were extracted from the QuickBird images and were used as the independent variables. The results showed that the BN model predicted PWD with high accuracy. In a sensitivity analysis, elevation (EL), the normal differential vegetation index (NDVI), the distance to settlements (DS) and the distance to roads (DR) were strongly associated with PWD prevalence, and slope (SL) exhibited the weakest association with PWD prevalence. The study showed that BN is an effective tool for modeling PWD prevalence and quantifying the impact of various factors.
文摘目的探讨海南省肺结核发病的时空特征及其相关因素,为制定海南省肺结核防控策略提供参考依据。方法整合2014—2023年海南各市县肺结核报告病例、气象、社会经济和卫生资源资料,构建5个层次递进的贝叶斯时空模型,逐步引入时空效应,采用集成嵌套拉普拉斯逼近(integrated nested Laplace approximation,INLA)算法进行贝叶斯推断,并依据偏差信息准则(deviance information criterion,DIC)、渡边赤池信息准则(Watanabe-Akaike information criterion,WAIC)和条件预测纵坐标(conditional predictive ordinates,CPO)选择最优模型,对肺结核发病的时空特征及影响因素进行分析。结果2014—2023年海南省各市县结核病发病风险存在空间异质性,模型估计的相对风险值范围为0.840~1.580,发病相对风险整体呈现东南沿海最高、西部次之、北部及中南部普遍较低的分布特征。2014—2023年发病年度相对风险围绕基准线低幅振荡,范围为0.968~1.029;月度相对风险则呈现季节特征,在1月和3月达到冬春季高峰,而在夏季的8、9月以及12月则降至基准以下。时空交互效应分析显示,全省肺结核发病风险整体呈下降趋势,区域间风险差异缩小。影响因素分析显示,气温(RR=0.988,95%CI:0.978~0.997)与气压(RR=0.994,95%CI:0.991~0.998)为保护因素,日照时数(RR=1.002,95%CI:1.001~1.003)是危险因素,农村人均纯收入为有统计学意义的保护因素,但其效应量极小。结论海南省肺结核发病呈现明显的时空异质性,受气象和社会经济因素影响。建议实施差异化防控,建立气象响应机制,并在发病高峰季节加强干预,同时巩固农村防控基础,以发挥保护作用。
文摘目的评估1990~2021年中国归因于生活方式和代谢因素缺血性脑卒中(ischemic stroke,IS)的疾病负担,并预测未来20年IS的疾病负担。方法收集全球疾病负担(global burden of disease,GBD)2021数据库中归因于生活方式和代谢因素的IS不同性别、年龄的死亡率、伤残调整寿命年(disability adjusted life years,DALY)率、年龄标准化死亡率(age-standardized mortality rate,ASMR)和年龄标准化伤残调整寿命年率(age-standardized rate of disability adjusted life years,ASDR)。使用Joinpoint回归分析IS的ASMR和ASDR的年度变化率和平均年度变化率。使用贝叶斯年龄-时期-队列(Bayesian age-period-cohort,BAPC)模型预测未来20年IS的ASMR和ASDR发展趋势。结果中国2021年归因于饮食风险、高空腹血糖、高低密度脂蛋白胆固醇(low-density lipoprotein cholesterol,LDL-C)、低体力劳动、烟草的IS的ASMR和ASDR均低于1990年,归因于高体质量指数(body mass index,BMI)的ASMR和ASDR高于1990年,归因于高收缩压的IS疾病负担最重。1990~2021年我国女性归因于高LDL-C和低体力活动的IS的ASMR和ASDR呈下降趋势,男性未见明显变化;男性归因于高收缩压的IS的ASMR和ASDR呈上升趋势,女性呈下降趋势;男性和女性归因于高BMI的IS的ASMR和ASDR呈上升趋势,男性IS的疾病负担要高于女性。我国IS的疾病负担随着年龄的增大而增加。未来20年我国归因于饮食风险、高收缩压、高空腹血糖、高LDL-C、低体力劳动、烟草的IS疾病负担逐步降低,归因于高BMI的IS疾病负担逐步上升。结论中国归因于饮食风险、高空腹血糖、高LDL-C、低体力劳动、烟草的IS疾病负担虽然持续呈下降趋势,但是IS的防治形式依旧严峻,归因于高BMI的IS疾病负担呈持续上升趋势,未来需针对重点人群(高龄、男性等)精准施策。
