Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Lianfen Qian"'
Autor:
Sara Schesser Bartra, Cherish Lorica, Lianfen Qian, Xin Gong, Wael Bahnan, Henry Barreras Jr., Rosmely Hernandez, Zhongwei Li, Gregory V. Plano, Kurt Schesser
Publikováno v:
Frontiers in Cellular and Infection Microbiology, Vol 9 (2019)
Yersinia pestis, the causative agent of plague, possesses a number of virulence mechanisms that allows it to survive and proliferate during its interaction with the host. To discover additional infection-specific Y. pestis factors, a transposon site
Externí odkaz:
https://doaj.org/article/638089bfffef4a839f30b5bebfd02c98
Publikováno v:
Combinatorial Chemistry & High Throughput Screening. 22:225-231
Background: Assisted reproductive techniques (ART) have been extensively used to treat infertility. Inaccurate prediction of a couple’s fertility often leads to lowered self-esteem for patients seeking ART treatment and causes fertility distress. O
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7c05d5e0ccf43cd4dd5f61b463437c3
https://doi.org/10.2174/1386207322666190404145448
https://doi.org/10.2174/1386207322666190404145448
Publikováno v:
Statistical Papers. 61:2313-2330
To incorporate the realized volatility in stock return, Hansen et al. (J Appl Econ 27:877–906, 2012) proposed a RealGARCH model and conjectured some theoretical properties about the quasi-maximum likelihood estimation (QMLE) for parameters in a log
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a115426cb7ae877e602be4564c126982
https://doi.org/10.1007/s00362-018-1051-8
https://doi.org/10.1007/s00362-018-1051-8
Autor:
Suojin Wang, Lianfen Qian
Publikováno v:
Computational Statistics & Data Analysis. 111:77-87
In analyzing longitudinal data, within-subject correlations are a major factor that affects statistical efficiency. Working with a partially linear model for longitudinal data, a subject-wise empirical likelihood based method that takes the within-su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c91cc8aafe926c19e3fb8997fa66259
https://doi.org/10.1016/j.csda.2017.02.001
https://doi.org/10.1016/j.csda.2017.02.001
Autor:
Lianfen Qian
Publikováno v:
SM Preventive Medicine and Public Health. 2:1-3
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d350065fe685f57740236d44ba2db6c
https://doi.org/10.36876/smpmph.1026
https://doi.org/10.36876/smpmph.1026
Autor:
Durga H. Kutal, Lianfen Qian
Publikováno v:
Stats
Volume 1
Issue 1
Pages 13-188
Volume 1
Issue 1
Pages 13-188
This paper considers a non-mixture cure model for right-censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Fré
chet susceptible distribution
chet susceptible distribution
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92ebe0f0d3ca5f974545127cd2e107bf
Autor:
Lianfen Qian, Durga H. Kutal
This paper considers a non-mixture cure model for right censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Fréchet susceptible distribution to evaluat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6edbcbc4b2401aa9690343b012bbec7a
Autor:
Yun-Xia Li, Lianfen Qian
Publikováno v:
Journal of Mathematical Analysis and Applications. 412:498-504
In this paper, we consider the likelihood ratio test for the scale and shape parameters in a piecewise continuous Weibull model with an unknown change point. Under the null hypothesis of no change in scale and shape parameters, we derive that the lik
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::795d3ac62cd854a24185ffe11f690d91
https://doi.org/10.1016/j.jmaa.2013.10.069
https://doi.org/10.1016/j.jmaa.2013.10.069
Publikováno v:
Communications in Statistics - Simulation and Computation. 43:1685-1699
In this article, we consider parameter estimation in the hazard rate with multiple change points in the presence of long-term survivors. We combine two methods: maximum likelihood based and martingale based, to estimate the change points in the hazar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8fae5fc0fa0a120943adc73e4a569a4
https://doi.org/10.1080/03610918.2012.742106
https://doi.org/10.1080/03610918.2012.742106
Publikováno v:
Statistics & Probability Letters. 83:1683-1691
This paper estimates the change-point for a piecewise hazard regression model in the presence of right censoring and long-term survivors. The maximum likelihood estimators of the change point and other parameters are shown to be consistent. The propo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec54f7419f7ca424fd3c28b71e24ac8e
https://doi.org/10.1016/j.spl.2013.03.026
https://doi.org/10.1016/j.spl.2013.03.026