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
The purpose of this paper is to analyze an accuracy design method for reconfigurable parallel manipulators including a 6-SPS and a 6-PSS parallel manipulator.An error analysis method,based on the module error model,wa...The purpose of this paper is to analyze an accuracy design method for reconfigurable parallel manipulators including a 6-SPS and a 6-PSS parallel manipulator.An error analysis method,based on the module error model,was used to express the relationship between the module error and the terminal error in the error transmission equation of the reconfigurable parallel manipulator.In addition,an error distribution method using a manufacturing and assembly difficulty coefficient was used to analyze each error module to determine a maximum terminal error.The error distribution result was then used to set up a reconfigurable parallel manipulator.Error experiments with a reconfigurable parallel manipulator show that the error analysis and distribution method for reconfigurable parallel manipulators are effective and the maximum terminal errors of the reconfigurable parallel manipulators are less than 50 μm.展开更多
The reconstruction of a parameter by the measurement of a random variable depending on the parameter is one of the main tasks in statistics. In statistical inference, the concept of a confidence distribution and, corr...The reconstruction of a parameter by the measurement of a random variable depending on the parameter is one of the main tasks in statistics. In statistical inference, the concept of a confidence distribution and, correspondingly, confidence density has often been loosely referred to as a distribution function on the parameter space that can represent confidence intervals of all levels for a parameter of interest. In this short note, the notion of statistically dual distributions is discussed. Based on properties of statistically dual distributions, a method for reconstructing the confidence density of a parameter is proposed.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 (Nos 50605035 and 10778625)the National High-Tech Research and Development Program (863) of China (No2006AA04Z133)
文摘The purpose of this paper is to analyze an accuracy design method for reconfigurable parallel manipulators including a 6-SPS and a 6-PSS parallel manipulator.An error analysis method,based on the module error model,was used to express the relationship between the module error and the terminal error in the error transmission equation of the reconfigurable parallel manipulator.In addition,an error distribution method using a manufacturing and assembly difficulty coefficient was used to analyze each error module to determine a maximum terminal error.The error distribution result was then used to set up a reconfigurable parallel manipulator.Error experiments with a reconfigurable parallel manipulator show that the error analysis and distribution method for reconfigurable parallel manipulators are effective and the maximum terminal errors of the reconfigurable parallel manipulators are less than 50 μm.
文摘The reconstruction of a parameter by the measurement of a random variable depending on the parameter is one of the main tasks in statistics. In statistical inference, the concept of a confidence distribution and, correspondingly, confidence density has often been loosely referred to as a distribution function on the parameter space that can represent confidence intervals of all levels for a parameter of interest. In this short note, the notion of statistically dual distributions is discussed. Based on properties of statistically dual distributions, a method for reconstructing the confidence density of a parameter is proposed.
