Zobrazeno 1 - 10 of 58 pro vyhledávání: '"M. Revan Özkale"'
4
A combination of ridge and Liu regressions for extreme learning machine
Autor: Hasan Yıldırım, M. Revan Özkale
Publikováno v: Soft computing.
WOS:000903228300002 PubMed ID:36573103 Extreme learning machine (ELM) as a type of feedforward neural network has been widely used to obtain beneficial insights from various disciplines and real-world applications. Despite the advantages like speed a
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8333502c9de95b25010a5a4ae5f3609b
https://pubmed.ncbi.nlm.nih.gov/36573103
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6
Bootstrap selection of ridge regularization parameter: a comparative study via a simulation study
Autor: M. Revan Özkale, Hüsniye Altuner
Publikováno v: Communications in Statistics - Simulation and Computation. :1-19
In multiple linear regressions, it is known that least-squares estimates of the parameters are likely to be too large in absolute value and possibly of wrong sign, if explanatory variables are corr...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4772469b2142287a2a084333fde30182
https://doi.org/10.1080/03610918.2021.1948574
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7
Stochastic restricted Liu predictors in linear mixed models
Autor: Özge Kuran, M. Revan Özkale
Publikováno v: Communications in Statistics - Simulation and Computation. 50:2561-2580
In this article, we propose the stochastic restricted Liu predictors by augmenting the stochastic restrictions to the linear mixed models. The Liu biasing parameter is selected via generalized cross validation (GCV) criterion. Comparisons between the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6caa04910390c25f0d9b8e407c547543
https://doi.org/10.1080/03610918.2021.1957110
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8
Comparison of deviance and ridge deviance residual-based control charts for monitoring Poisson profiles
Autor: Ulduz Mammadova, M. Revan Özkale
Publikováno v: Communications in Statistics - Simulation and Computation. 52:826-853
Ridge estimator is one of the solutions for the multicollinearity problem caused by the absence of independency among predictors. Since the ridge estimator depends on the ridge biasing constant, a ...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::919bcaab1d049df16dce3f6335c228de
https://doi.org/10.1080/03610918.2020.1870693
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9
Improvement of mixed predictors in linear mixed models
Autor: M. Revan Özkale, Özge Kuran
Publikováno v: J Appl Stat
In this paper, we introduce stochastic-restricted Liu predictors which will be defined by combining in a special way the two approaches followed in obtaining the mixed predictors and the Liu predictors in the linear mixed models. Superiorities of the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e6dc2fa8cdd053224bcff949facc24e
https://pubmed.ncbi.nlm.nih.gov/35707446
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10
Usage of the GO estimator in high dimensional linear models
Autor: Murat Genç, M. Revan Özkale
Publikováno v: Computational Statistics. 36:217-239
This paper discusses simultaneous parameter estimation and variable selection and presents a new penalized regression method. The method is based on the idea that the coefficient estimates are shrunken towards a predetermined coefficient vector which
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::07846bf6c7514bff8e5d27715333e59a
https://doi.org/10.1007/s00180-020-01001-2
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