Longitudinal data often occur in follow-up studies, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. We propose a semiparamet...Longitudinal data often occur in follow-up studies, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. We propose a semiparametric mixed effect model with time-varying latent effects in the analysis of longitudinal data with informative observation times and a dependent terminal event. Estimating equation approaches are developed for parameter estimation, and asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a bladder cancer study is provided.展开更多
An ensemble-based assimilation system that used the MASINGAR ink-2 （Model of Aerosol Species IN the Global AtmospheRe Mark 2） dust forecasting model and satellite-derived aerosol optical thickness （AOT） data. proc...An ensemble-based assimilation system that used the MASINGAR ink-2 （Model of Aerosol Species IN the Global AtmospheRe Mark 2） dust forecasting model and satellite-derived aerosol optical thickness （AOT） data. processed in the JAXA （Japan Aerospace Exploration Agency） Satellite Monitoring for Environmental Studies （JASMES） system with MODIS （Moderate Resolution Imaging Spectroradiometer） observations. was used to quantify the impact of assimilation on forecasts of a severe Asian dust storm during May 10-13. 2011. The modeled bidirectional reflectance function and observed vegetation index employed in JASMES enable AOT retrievals in areas of high surface reflectance, making JASMES effective for dust forecasting and early warning by enabling assimilations in dust storm source regions. Forecasts both with and without assimilation were validated using PM^0 observations from China, Korea, and Japan in the TEMM WG1 dataset. Only the forecast with assimilation successfully captured the contrast between the core and tail of the dust storm by increasing the AOT around the core by 70-150% and decreasing it around the tail by 20-30% in the 18-h forecast. The forecast with assimilation improved the agreement with observed PMlo concentrations, but the effect was limited at downwind sites in Korea and Japan because of the lack of observational constraints for a mis-forecasted dust storm due to cloud.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos. 11231010, 11171330 and 11201315)Key Laboratory of Random Complex Structures and Data Science, Chinese Academy of Sciences (Grant No. 2008DP173182)Beijing Center for Mathematics and Information Interdisciplinary Sciences
文摘Longitudinal data often occur in follow-up studies, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. We propose a semiparametric mixed effect model with time-varying latent effects in the analysis of longitudinal data with informative observation times and a dependent terminal event. Estimating equation approaches are developed for parameter estimation, and asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a bladder cancer study is provided.
文摘An ensemble-based assimilation system that used the MASINGAR ink-2 （Model of Aerosol Species IN the Global AtmospheRe Mark 2） dust forecasting model and satellite-derived aerosol optical thickness （AOT） data. processed in the JAXA （Japan Aerospace Exploration Agency） Satellite Monitoring for Environmental Studies （JASMES） system with MODIS （Moderate Resolution Imaging Spectroradiometer） observations. was used to quantify the impact of assimilation on forecasts of a severe Asian dust storm during May 10-13. 2011. The modeled bidirectional reflectance function and observed vegetation index employed in JASMES enable AOT retrievals in areas of high surface reflectance, making JASMES effective for dust forecasting and early warning by enabling assimilations in dust storm source regions. Forecasts both with and without assimilation were validated using PM^0 observations from China, Korea, and Japan in the TEMM WG1 dataset. Only the forecast with assimilation successfully captured the contrast between the core and tail of the dust storm by increasing the AOT around the core by 70-150% and decreasing it around the tail by 20-30% in the 18-h forecast. The forecast with assimilation improved the agreement with observed PMlo concentrations, but the effect was limited at downwind sites in Korea and Japan because of the lack of observational constraints for a mis-forecasted dust storm due to cloud.
