Zobrazeno 1 - 10
of 92
pro vyhledávání: '"QIQING YU"'
Autor:
Qiqing Yu
Publikováno v:
Journal of Nonparametric Statistics. 35:266-282
Publikováno v:
Journal of Chemometrics. 37
Autor:
Qiqing Yu
Publikováno v:
Lifetime Data Analysis. 27:662-678
We carry out parametric inferences to a breast cancer data set which is right censored using the uniform distribution U(a, b). Under right censoring, it is rare that one can find the explicit solution to the maximum likelihood estimator (MLE) under t
Autor:
Qiqing Yu
Publikováno v:
WSEAS TRANSACTIONS ON SYSTEMS. 20:124-132
Suppose that the observations are i.i.d. from a density f(.; θ), where θ is an identifiable parameter. One expects that the maximum likelihood estimator of θ is consistent. But its consistency proof is non-trivial and various sufficient conditions
Autor:
Qiqing Yu
Publikováno v:
WSEAS TRANSACTIONS ON MATHEMATICS. 21:68-70
In this short note, we consider interval estimation for the parameters under the uniform distribution U(a; b). We study two approaches: (1) based on a Wald-type statistic, (2) based on a pivotal statistic. We show that the first approach in its commo
Autor:
Qiqing Yu
Publikováno v:
The Open Mathematics, Statistics and Probability Journal. 10:21-27
Objective: We studied the consistency of the semi-parametric maximum likelihood estimator (SMLE) under the Cox regression model with right-censored (RC) data. Methods: Consistency proofs of the MLE are often based on the Shannon-Kolmogorov inequality
Autor:
Junyi Dong, Qiqing Yu
Publikováno v:
Communications in Statistics - Theory and Methods. 51:116-134
The consistency of various estimators under the semi-parametric linear regression model and the standard right censorship model (SPLRRC model) has been studied under various assumptions sin...
Publikováno v:
Communications in Statistics - Simulation and Computation. 51:3955-3974
We propose a new approach to simultaneously test the assumptions of independence and goodness-of-fit for a multiple linear regression model Y=β′X+W, say H0, vs. H1: H0 is false. Our approach is bas...
Autor:
Junyi Dong, Qiqing Yu
Publikováno v:
Journal of Statistical Planning and Inference. 201:58-70
Let Z be the covariate vector and Y be the response variable with the joint cumulative distribution function F Y , Z . Given a random sample from F Y , Z , in order to analyze the data based on a certain proportional hazards (PH) model, say Θ 0 , on