An Efficient and Robust Variable Selection Method for Longitudinal Generalized Linear Models

来源 :第八届工业与应用数学国际大会 | 被引量 : 0次 | 上传用户:shyandi123
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
  This paper presents a new efficient and robust smooth-threshold generalized estimating equations for generalized linear models(GLMs)with longitudinal data.
其他文献
  Multi-canonical Monte Carlo(MMC)has been used to estimate small failure probabilities in various engineering problems.
会议
  Firstly I fitted a group of five-minute stock data with ARIMA+GARCH model as tool,after that I acquired daily volatility based on realized power variation t
会议
  The problem consists in maximizing the expectation of some reward function among all martingale measures under some marginal constraints.We establish the du
会议
  In this paper,we consider the choice of pilot estimators for the single-index varying-coefficient model,which may result in radically different estimators,a
会议
  We study the weak approximation for non-smooth functionals of(reflected)stochastic differential equations with irregular drift and constant diffusion coeffi
会议
  This paper mainly discusses the pth moment asymptotic stability and the exponential stability of nonlinear stochastic functional differential equations(SFDE
会议
  A new estimation procedure based on modal regression is proposed for single-index varying-coefficient models.The proposed method achieves better robustness
会议
  In this paper,we propose the penalized weighted composite quantile regression estimation for linear model when the covariates are missing at random.
会议
  In this paper,we investigate a new train of thought to lead the model selection consistency of lasso.One important but more standard and much weaker conditi
会议
  The system generate events in random moments and with random effects.Any deviation from the regularity of events or results significantly different from the
会议