Detection of the best model selection criterion in Gaussian graphical model

2017-06-01

Suggestions

Detection of the distribution and parameter estimation for the departing connectivity in biological networks
Odunsi, Omolola Dorcas; Purutçuoğlu Gazi, Vilda; Department of Statistics (2014)
The connectivity density is one of the characteristics features in the topology of the network. This density describes the total number of the in-degree and out-degree of a node in a system. In a network, the in-degree or arriving connectivity represents the number of links coming to a target gene and the out-degree or departing connectivity stands for the number of links departing from the target gene. For biological networks, the density of the in-degree is represented by the exponential distribution and ...
Detection of component composition mismatch with axiomatic design
Toğay, Cengiz; SUNDAR, Gayathri; Doğru, Ali Hikmet (2006-04-02)
This paper presents a software component composition methodology based on Axiomatic Design theory and Design Structure Matrix. The methodology we propose helps overcome anomalies and functional problems such as deadlock. Our approach can be described in two steps. First, we decompose the system to detect coupled components by using the Design Structure Matrix. Secondly, we represent attribute and method dependencies of the coupled components to identify issues during software composition using Design Matrix...
Detection of a sinusoid by the MRAS approach and input design for parallel MRAS.
Tuncay, arzu; Department of Electrical Engineering (1985)
Detection of Unreliable measurements in long term time series via data mining techniques case in Turkish climate data
Yazıcı, Ceyda; Purutçuoğlu Gazi, Vilda; Yozgatlıgil, Ceylan; İyigün, Cem; Batmaz, İnci (2013-06-28)
Detection of outliers using Fouriertransform
Akkuş, Ekin Can; Purutçuoğlu Gazi, Vilda; Ağraz, Melih (null; 2017-12-06)
Citation Formats
V. Purutçuoğlu Gazi, “Detection of the best model selection criterion in Gaussian graphical model,” 2017, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/78777.