Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Tuac, Yetkin"'
Autor:
Sayan, Mutlay1 (AUTHOR) msayan@bwh.harvard.edu, Tuac, Yetkin2 (AUTHOR), Akgul, Mahmut3 (AUTHOR), Kucukcolak, Samet4 (AUTHOR), Tjio, Elza5 (AUTHOR), Akbulut, Dilara6 (AUTHOR), Chen, Luke W.1 (AUTHOR), Yang, David D.1 (AUTHOR), Moningi, Shalini1 (AUTHOR), Leeman, Jonathan E.1 (AUTHOR), Orio, Peter F.1 (AUTHOR), Nguyen, Paul L.1 (AUTHOR), D'Amico, Anthony V.1 (AUTHOR), Aktan, Cagdas7 (AUTHOR)
Publikováno v:
International Journal of Molecular Sciences. Aug2024, Vol. 25 Issue 16, p8913. 13p.
Autor:
Tuaç, Yetkin, Arslan, Olcay
Parameter estimation and the variable selection are two pioneer issues in regression analysis. While traditional variable selection methods require prior estimation of the model parameters, the penalized methods simultaneously carry on parameter esti
Externí odkaz:
http://arxiv.org/abs/2108.13755
Autor:
Sayan, Mutlay1 (AUTHOR) msayan@bwh.harvard.edu, Tuac, Yetkin2 (AUTHOR), Kucukcolak, Samet3 (AUTHOR), Rowan, Mary D.1 (AUTHOR), Pratt, Grace K.1 (AUTHOR), Aktan, Cagdas4 (AUTHOR), Tjio, Elza5 (AUTHOR), Akbulut, Dilara6 (AUTHOR), Moningi, Shalini1 (AUTHOR), Leeman, Jonathan E.1 (AUTHOR), Orio, Peter F.1 (AUTHOR), Nguyen, Paul L.1 (AUTHOR), D'Amico, Anthony V.1 (AUTHOR), Akgul, Mahmut7 (AUTHOR)
Publikováno v:
Cancers. May2024, Vol. 16 Issue 10, p1871. 11p.
Autor:
Sayan, Mutlay1 (AUTHOR) msayan@bwh.harvard.edu, Tuac, Yetkin2 (AUTHOR) yetkin.tuac@ankara.edu.tr, Akgul, Mahmut3 (AUTHOR), Pratt, Grace K.1 (AUTHOR), Rowan, Mary D.1 (AUTHOR), Akbulut, Dilara4 (AUTHOR), Kucukcolak, Samet5 (AUTHOR), Tjio, Elza6 (AUTHOR), Moningi, Shalini1 (AUTHOR), Leeman, Jonathan E.1 (AUTHOR), Orio, Peter F.1 (AUTHOR), Nguyen, Paul L.1 (AUTHOR), D'Amico, Anthony V.1 (AUTHOR), Aktan, Cagdas7 (AUTHOR)
Publikováno v:
Cancers. Apr2024, Vol. 16 Issue 7, p1248. 11p.
In countries with a severe outbreak of COVID-19, most governments are considering whether anti-transmission measures are worth social and economic costs. The seriousness of economic costs such as the closure of some workplaces, unemployment, reductio
Externí odkaz:
http://arxiv.org/abs/2012.15302
Linear regression models are useful statistical tools to analyze data sets in several different fields. There are several methods to estimate the parameters of a linear regression model. These methods usually perform under normally distributed and un
Externí odkaz:
http://arxiv.org/abs/2008.03282
In the linear regression model with possibly autoregressive errors, we propose a family of nonparametric tests for regression under a nuisance autoregression. The tests avoid the estimation of nuisance parameters, in contrast to the tests proposed in
Externí odkaz:
http://arxiv.org/abs/2007.12124
Marshall-Olkin Extended Burr XII (MOEBXII) distribution family, which is a generalization of Burr XII distribution proposed by Al-Saiari et al. [1] , is a flexible distribution that can be used in many fields such as actuarial science, economics, lif
Externí odkaz:
http://arxiv.org/abs/1804.08345
In this article, we consider the parameter estimation of regression model with pth order autoregressive (AR(p)) error term. We use the Maximum Lq-likelihood (MLq) estimation method that is proposed by Ferrari and Yang (2010a), as a robust alternative
Externí odkaz:
http://arxiv.org/abs/1804.07600
In this paper, we consider a linear regression model with AR(p) error terms with the assumption that the error terms have a t distribution as a heavy tailed alternative to the normal distribution. We obtain the estimators for the model parameters by
Externí odkaz:
http://arxiv.org/abs/1710.04451