Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Comparison of two inference approaches in Gaussian graphical models
Date
2017-04-01
Author
Purutçuoğlu Gazi, Vilda
AYYILDIZ DEMİRCİ, EZGİ
Wit, Ernst
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
1
views
0
downloads
Introduction: The Gaussian Graphical Model (GGM) is one of the well-known probabilistic models which is based on the conditional independency of nodes in the biological system. Here, we compare the estimates of the GGM parameters by the graphical lasso (glasso) method and the threshold gradient descent (TGD) algorithm.
Subject Keywords
Clinical Biochemistry
,
Biochemistry
,
Molecular Biology
,
Biochemistry, medical
URI
https://hdl.handle.net/11511/40762
Journal
TURKISH JOURNAL OF BIOCHEMISTRY-TURK BIYOKIMYA DERGISI
DOI
https://doi.org/10.1515/tjb-2016-0298
Collections
Department of Statistics, Article