Linear Mixed Models and Data Science Investigations

Date

2017-03-08

Author

Gökalp Yavuz, Fulya
Arslan, Olçay

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https://hdl.handle.net/11511/82632

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Linear mixed model with Laplace distribution (LLMM) Gökalp Yavuz, Fulya (2018-03-01) Linear mixed modeling (LMM) is a comprehensive technique used for clustered, panel and longitudinal data. The main assumption of classical LMM is having normally distributed random effects and error terms. However, there are several situations for that we need to use heavier tails distributions than the (multivariate) normal to handle outliers and/or heavy tailness in data. In this study, we focus on LMM using the multivariate Laplace distribution which is known as the heavy tailed alternative to the normal...
Linear approximations and extensions to distance based multicriteria sorting methods Taş, Hasan; Karasakal, Esra; Department of Industrial Engineering (2022-8-26) Multicriteria sorting is the assignment of alternatives to predefined preference ordered classes. In this thesis, linear approximations to nearest centroid and distance-based multicriteria sorting methods are studied. Three studies are conducted. The first study is the linearization of a nearest centroid based method. In the second study, the nearest centroid classifier method is investigated under monotonic centroids and a new linear programming model is developed based on the feasibility and redundancy co...
Linear and nonlinear model updating of reinforced concrete T-beam bridges using artificial neural networks Hasançebi, Oğuzhan (2013-04-01) The key parameters affecting dynamic and static responses of structural systems often change during their life cycles due to aging, deterioration, damage and rehabilitation. Model updating is a major research field that investigates numerical methods to improve simulation ability of finite element (FE) models by identifying the modified parameters in structural systems based on data collected from field experiments and/or laboratory tests. In this paper, artificial neural networks (ANNs) are used to develop...
Linear parameter varying control for autonomous systems: methods and application examples Çalış, Fatih; Schmidt, Klaus Verner; Department of Electrical and Electronics Engineering (2022-8-24) Linear parameter varying (LPV) systems are nonlinear systems which can be modelled as linear systems whose parameters change as a function of different "scheduling parameters". In other words, the dynamics of the LPV systems change during the operation hence they require a parameter dependent controller. Although classical gain-scheduling approaches satisfy some performance criteria for constant dynamics, they don't guarantee stability while the scheduling parameter is changing. On the other hand, H∞-norm b...
Linear Canonical Domains and Degrees of Freedom of Signals and Systems Öktem, Sevinç Figen (2016-01-01) We discuss the relationships between linear canonical transform (LCT) domains, fractional Fourier transform (FRT) domains, and the space-frequency plane. In particular, we show that LCT domains correspond to scaled fractional Fourier domains and thus to scaled oblique axes in the space-frequency plane. This allows LCT domains to be labeled and monotonically ordered by the corresponding fractional order parameter and provides a more transparent view of the evolution of light through an optical system modeled...

Citation Formats

F. Gökalp Yavuz and O. Arslan, “Linear Mixed Models and Data Science Investigations,” 2017, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/82632.