A New Class of Minimum Power Divergence Estimators with Applications to Cancer Surveillance [0.03%]
一类最小功率分歧估计量及其在癌症监测中的应用
Nirian Martín,Yi Li
Nirian Martín
The Annual Percent Change (APC) has been adopted as a useful measure for analyzing the changing trends of cancer mortality and incidence rates by the NCI SEER program. Difficulties, however, arise when comparing the sample APCs between two ...
A test of location for exchangeable multivariate normal data with unknown correlation [0.03%]
未知相关性下交联多元正态数据的均值检验问题
Dean Follmann,Michael Proschan
Dean Follmann
We consider the problem of testing whether the common mean of a single n-vector of multivariate normal random variables with known variance and unknown common correlation ρ is zero. We derive the standardized likelihood ratio test for know...
Multivariate Failure Times Regression with a Continuous Auxiliary Covariate [0.03%]
具有连续辅助协变量的多元失效时间回归分析
Yanyan Liu,Yuanshan Wu,Haibo Zhou
Yanyan Liu
How to take advantage of the available auxiliary covariate information when the primary covariate of interest is not measured is a frequently encountered question in biomedical study. In this paper, we consider the multivariate failure time...
Anna Klimova,Tamás Rudas,Adrian Dobra
Anna Klimova
The paper considers general multiplicative models for complete and incomplete contingency tables that generalize log-linear and several other models and are entirely coordinate free. Sufficient conditions of the existence of maximum likelih...
Malay Ghosh,Georgios Papageorgiou,Janet Forrester
Malay Ghosh
Based on the notion of predictive influence functions, the paper develops multivariate limited translation hierarchical Bayes estimators of the normal mean vector which serve as a compromise between the hierarchical Bayes and maximum likeli...
Some theoretical properties of Silverman's method for Smoothed functional principal component analysis [0.03%]
Silverman平滑函数主成分分析法的若干理论性质
Xin Qi,Hongyu Zhao
Xin Qi
Principal component analysis (PCA) is one of the key techniques in functional data analysis. One important feature of functional PCA is that there is a need for smoothing or regularizing of the estimated principal component curves. Silverma...
Multivariate logistic regression with incomplete covariate and auxiliary information [0.03%]
含缺失协变量的多逻辑回归与辅助信息
Sanjoy K Sinha,Nan M Laird,Garrett M Fitzmaurice
Sanjoy K Sinha
In this article, we propose and explore a multivariate logistic regression model for analyzing multiple binary outcomes with incomplete covariate data where auxiliary information is available. The auxiliary data are extraneous to the regres...
Sieve Maximum Likelihood Estimation for Doubly Semiparametric Zero-Inflated Poisson Models [0.03%]
双半参数零膨胀泊松模型的筛分极大似然估计方法
Xuming He,Hongqi Xue,Ning-Zhong Shi
Xuming He
For nonnegative measurements such as income or sick days, zero counts often have special status. Furthermore, the incidence of zero counts is often greater than expected for the Poisson model. This article considers a doubly semiparametric ...
Hao Helen Zhang,Wenbin Lu,Hansheng Wang
Hao Helen Zhang
Semiparametric linear transformation models have received much attention due to its high flexibility in modeling survival data. A useful estimating equation procedure was recently proposed by Chen et al. (2002) for linear transformation mod...
Guang Cheng,Michael R Kosorok
Guang Cheng
The penalized profile sampler for semiparametric inference is an extension of the profile sampler method [9] obtained by profiling a penalized log-likelihood. The idea is to base inference on the posterior distribution obtained by multiplyi...