Survival of HIV/AIDS patients is crucially dependent on comprehensive and targeted medical interventions such as supply of antiretroviral therapy and monitoring disease progression with CD4 T-cell counts. Statistical ...Survival of HIV/AIDS patients is crucially dependent on comprehensive and targeted medical interventions such as supply of antiretroviral therapy and monitoring disease progression with CD4 T-cell counts. Statistical modelling approaches are helpful towards this goal. This study aims at developing Bayesian joint models with assumed generalized error distribution (GED) for the longitudinal CD4 data and two accelerated failure time distributions, Lognormal and loglogistic, for the survival time of HIV/AIDS patients. Data are obtained from patients under antiretroviral therapy follow-up at Shashemene referral hospital during January 2006-January 2012 and at Bale Robe general hospital during January 2008-March 2015. The Bayesian joint models are defined through latent variables and association parameters and with specified non-informative prior distributions for the model parameters. Simulations are conducted using Gibbs sampler algorithm implemented in the WinBUGS software. The results of the analyses of the two different data sets show that distributions of measurement errors of the longitudinal CD4 variable follow the generalized error distribution with fatter tails than the normal distribution. The Bayesian joint GED loglogistic models fit better to the data sets compared to the lognormal cases. Findings reveal that patients’ health can be improved over time. Compared to the males, female patients gain more CD4 counts. Survival time of a patient is negatively affected by TB infection. Moreover, increase in number of opportunistic infection implies decline of CD4 counts. Patients’ age negatively affects the disease marker with no effects on survival time. Improving weight may improve survival time of patients. Bayesian joint models with GED and AFT distributions are found to be useful in modelling the longitudinal and survival processes. Thus we recommend the generalized error distributions for measurement errors of the longitudinal data under the Bayesian joint modelling. Further studies may investigate the models with various types of shared random effects and more covariates with predictions.展开更多
Logarithmic general error distribution is an extension of lognormal distribution. In this paper, with optimal norming constants the higher-order expansion of distribution of partial maximum of logarithmic general erro...Logarithmic general error distribution is an extension of lognormal distribution. In this paper, with optimal norming constants the higher-order expansion of distribution of partial maximum of logarithmic general error distribution is derived.展开更多
In this paper, the weighted Kolmogrov-Smirnov, Cramer von-Miss and the Anderson Darling test statistics are considered as goodness of fit tests for the generalized Rayleigh interval grouped data. An extensive simulati...In this paper, the weighted Kolmogrov-Smirnov, Cramer von-Miss and the Anderson Darling test statistics are considered as goodness of fit tests for the generalized Rayleigh interval grouped data. An extensive simulation process is conducted to evaluate their controlling of type 1 error and their power functions. Generally, the weighted Kolmogrov-Smirnov test statistics show a relatively better performance than both, the Cramer von-Miss and the Anderson Darling test statistics. For large sample values, the Anderson Darling test statistics cannot control type 1 error but for relatively small sample values it indicates a better performance than the Cramer von-Miss test statistics. Best selection of the test statistics and highlights for future studies are also explored.展开更多
GARCH model under the assumption of generalized error distribution(GED) is used to obtain the daily-volatility of log-return.The parameters are estimated by adaptive genetic algorithm.The tests of VaR and CVaR show th...GARCH model under the assumption of generalized error distribution(GED) is used to obtain the daily-volatility of log-return.The parameters are estimated by adaptive genetic algorithm.The tests of VaR and CVaR show that GARCH-GED model is valid for financial risk measure.展开更多
配电网接入分布式电源、储能系统后,其主动控制系统须同时兼顾全局优化与局部自治控制的要求,具有对各分布式电源、储能以及配电网运行方式的主动调节能力。提出馈线控制误差(feeder control error,FCE)指标,实时描述主动配电网实际运...配电网接入分布式电源、储能系统后,其主动控制系统须同时兼顾全局优化与局部自治控制的要求,具有对各分布式电源、储能以及配电网运行方式的主动调节能力。提出馈线控制误差(feeder control error,FCE)指标,实时描述主动配电网实际运行状态与最优运行状态的差异,并基于FCE提出了定交换功率控制和追踪目标控制两种控制模式下的主动配电网的协调控制,实现全局优化基础上的局部协调控制。最后通过算例仿真分析,验证了基于FCE的主动配电网协调控制模式的有效性。展开更多
文摘Survival of HIV/AIDS patients is crucially dependent on comprehensive and targeted medical interventions such as supply of antiretroviral therapy and monitoring disease progression with CD4 T-cell counts. Statistical modelling approaches are helpful towards this goal. This study aims at developing Bayesian joint models with assumed generalized error distribution (GED) for the longitudinal CD4 data and two accelerated failure time distributions, Lognormal and loglogistic, for the survival time of HIV/AIDS patients. Data are obtained from patients under antiretroviral therapy follow-up at Shashemene referral hospital during January 2006-January 2012 and at Bale Robe general hospital during January 2008-March 2015. The Bayesian joint models are defined through latent variables and association parameters and with specified non-informative prior distributions for the model parameters. Simulations are conducted using Gibbs sampler algorithm implemented in the WinBUGS software. The results of the analyses of the two different data sets show that distributions of measurement errors of the longitudinal CD4 variable follow the generalized error distribution with fatter tails than the normal distribution. The Bayesian joint GED loglogistic models fit better to the data sets compared to the lognormal cases. Findings reveal that patients’ health can be improved over time. Compared to the males, female patients gain more CD4 counts. Survival time of a patient is negatively affected by TB infection. Moreover, increase in number of opportunistic infection implies decline of CD4 counts. Patients’ age negatively affects the disease marker with no effects on survival time. Improving weight may improve survival time of patients. Bayesian joint models with GED and AFT distributions are found to be useful in modelling the longitudinal and survival processes. Thus we recommend the generalized error distributions for measurement errors of the longitudinal data under the Bayesian joint modelling. Further studies may investigate the models with various types of shared random effects and more covariates with predictions.
基金Supported by the National Natural Science Foundation of China(11171275)the Natural Science Foundation Project of CQ(cstc2012jj A00029)the Doctoral Grant of University of Shanghai for Science and Technology(BSQD201608)
文摘Logarithmic general error distribution is an extension of lognormal distribution. In this paper, with optimal norming constants the higher-order expansion of distribution of partial maximum of logarithmic general error distribution is derived.
文摘In this paper, the weighted Kolmogrov-Smirnov, Cramer von-Miss and the Anderson Darling test statistics are considered as goodness of fit tests for the generalized Rayleigh interval grouped data. An extensive simulation process is conducted to evaluate their controlling of type 1 error and their power functions. Generally, the weighted Kolmogrov-Smirnov test statistics show a relatively better performance than both, the Cramer von-Miss and the Anderson Darling test statistics. For large sample values, the Anderson Darling test statistics cannot control type 1 error but for relatively small sample values it indicates a better performance than the Cramer von-Miss test statistics. Best selection of the test statistics and highlights for future studies are also explored.
文摘GARCH model under the assumption of generalized error distribution(GED) is used to obtain the daily-volatility of log-return.The parameters are estimated by adaptive genetic algorithm.The tests of VaR and CVaR show that GARCH-GED model is valid for financial risk measure.
文摘配电网接入分布式电源、储能系统后,其主动控制系统须同时兼顾全局优化与局部自治控制的要求,具有对各分布式电源、储能以及配电网运行方式的主动调节能力。提出馈线控制误差(feeder control error,FCE)指标,实时描述主动配电网实际运行状态与最优运行状态的差异,并基于FCE提出了定交换功率控制和追踪目标控制两种控制模式下的主动配电网的协调控制,实现全局优化基础上的局部协调控制。最后通过算例仿真分析,验证了基于FCE的主动配电网协调控制模式的有效性。
