Sequential Shrinkage Estimate for COX Regression Models with Uncertain Number of Effective Variables

In the applications of COX regression models, we always encounter data sets that contain too many variables that only a few of them contribute to the model. Therefore, it will waste much more samples to estimate the “noneffective” variables in the inference. In this paper, we use a sequential procedure for constructing the fixed size confidence set for the “effective” parameters to the model based on an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size. Fixed design is considered for numerical simulation. The strong consistency, asymptotic distributions and convergence rates of estimates under the fixed design are obtained. In addition, the sequential procedure is shown to be asymptotically optimal in the sense of Chow and Robbins (1965).

A Sequential Shrinkage Estimating Method for Tobit Regression Model

In the applications of Tobit regression models we always encounter the data sets which contain too many variables that only a few of them contribute to the model. Therefore, it will waste much more samples to estimate the “non-effective” variables in the inference. In this paper, we use a sequential procedure for constructing the fixed size confidence set for the “effective” parameters to the model by using an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size based on Tobit regression model. Fixed design is considered for numerical simulation.

A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests

Relationships among productivity,leaf phenology,and seasonal variation in moisture and light availability are poorly understood for evergreen broadleaved tropical/subtropical forests,which contribute 25% of terrestrial productivity.On the one hand,as moisture availability declines,trees shed leaves to reduce transpiration and the risk of hydraulic failure.On the other hand,increases in light availability promote the replacement of senescent leaves to increase productivity.Here,we provide a comprehensive framework that relates the seasonality of climate,leaf abscission,and leaf productivity across the evergreen broadleaved tropical/subtropical forest biome.The seasonal correlation between rainfall and light availability varies from strongly negative to strongly positive across the tropics and maps onto the seasonal correlation between litterfall mass and productivity for 68 forests.Where rainfall and light covary positively,litterfall and productivity also covary positively and are always greater in the wetter sunnier season.Where rainfall and light covary negatively,litterfall and productivity are always greater in the drier and sunnier season if moisture supplies remain adequate;otherwise productivity is smaller in the drier sunnier season.This framework will improve the representation of tropical/subtropical forests in Earth system models and suggests how phenology and productivity will change as climate change alters the seasonality of cloud cover and rainfall across tropical/subtropical forests.

Discovery of CECR2 Bromodomain Inhibitors with High Selectivities over BPTF Bromodomain

Cat's eye syndrome chromosome candidate 2 bromodomain(CECR2 BRD)and Bromodomain PHD transcription factor bromodomain(BPTF BRD)are the same subfamily proteins,both of which are highly conserved in sequence and binding pockets.Challenges remain in the development of small molecules to inhibit one of the two bromodomains(BRDs),in view of each subtype may possess unique physiological and pathological functions.There is still a lack of effective selective inhibitors of CECR2 BRD,which makes it difficult to fully understand the pathogenesis of CECR2-BRD in diseases,especially cancers.Herein,we report our efforts to discover a series of highly selective CECR2 BRD inhibitors over BPTF BRD based on TP-248.Structure-based molecular optimization led to the discovery of DC-CEi-26,whose IC_(50) for CECR2 BRD was 96.7±14.9 nmol/L and selectivity was up to 590×over BPTF BRD.DC-CEi-26 showed weak potencies for other classic BRDs in different subfamily,which may serve as a chemical probe for CECR2 BRD biological research.