Changwon Lim,Pranab K Sen,Shyamal D Peddada
Changwon Lim
Toxicologists and pharmacologists often describe toxicity of a chemical using parameters of a nonlinear regression model. Thus estimation of parameters of a nonlinear regression model is an important problem. The estimates of the parameters...
Arnab Maity,Michael Sherman
Arnab Maity
Spatial modeling is typically composed of a specification of a mean function and a model for the correlation structure. A common assumption on the spatial correlation is that it is isotropic. This means that the correlation between any two ...
A Hybrid Geometric Phase II/III Clinical Trial Design based on Treatment Failure Time and Toxicity [0.03%]
基于治疗失败时间和毒性的混合几何二期和三期临床试验设计
Peter F Thall,Hoang Q Nguyen,Xuemei Wang et al.
Peter F Thall et al.
The problem of comparing several experimental treatments to a standard arises frequently in medical research. Various multi-stage randomized phase II/III designs have been proposed that select one or more promising experimental treatments a...
Bayesian Experimental Design for Long-Term Longitudinal HIV Dynamic Studies [0.03%]
纵向HIV动态长期实验的贝叶斯设计方法研究
Yangxin Huang,Hulin Wu
Yangxin Huang
The study of HIV dynamics is one of the most important developments in recent AIDS research for understanding the pathogenesis of HIV-1 infection and antiviral treatment strategies. Currently a large number of AIDS clinical trials on HIV dy...
Kernel Smoothing Density Estimation when Group Membership is Subject to Missing [0.03%]
分组情况缺失下的核密度估计方法研究
Wan Tang,Hua He,Douglas Gunzler
Wan Tang
Density function is a fundamental concept in data analysis. Nonparametric methods including kernel smoothing estimate are available if the data is completely observed. However, in studies such as diagnostic studies following a two-stage des...
Semiparametric inference of proportional odds model based on randomly truncated data [0.03%]
基于随机截断数据的比例优势模型的半参数推断
Rajeshwari Sundaram
Rajeshwari Sundaram
This paper studies the estimation in the proportional odds model based on randomly truncated data. The proposed estimators for the regression coefficients include a class of minimum distance estimators defined through weighted empirical odd...
Dimension reduced kernel estimation for distribution function with incomplete data [0.03%]
缺失数据下分布函数的降维核估计方法研究
Zonghui Hu,Dean A Follmann,Jing Qin
Zonghui Hu
This work focuses on the estimation of distribution functions with incomplete data, where the variable of interest Y has ignorable missingness but the covariate X is always observed. When X is high dimensional, parametric approaches to inco...
Kion Kim,Damla Sentürk,Runze Li
Kion Kim
We consider the recent history functional linear models, relating a longitudinal response to a longitudinal predictor where the predictor process only in a sliding window into the recent past has an effect on the response value at the curre...
Ao Yuan,Paul Bezandry,George Bonney
Ao Yuan
In clinical trials, several competing treatments are often carried out in the same trial period. The goal is to assess the performances of these different treatments according to some optimality criterion and minimize risks to the patients ...
Best Invariant and Minimax Estimation of Quantiles in Finite Populations [0.03%]
有限总体中分位数的优良不变和极小极大估计
Yaakov Malinovsky,Yosef Rinott
Yaakov Malinovsky
The theoretical literature on quantile and distribution function estimation in infinite populations is very rich, and invariance plays an important role in these studies. This is not the case for the commonly occurring problem of estimation...