Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Inference of the biological systems via L1-penalized lasso regression
Date
2013-06-01
Author
Purutçuoğlu Gazi, Vilda
Metadata
Show full item record
Item Usage Stats
25
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/83372
Conference Name
29th Meeting of Statisticians (01 Haziran 2013)
Collections
Unverified, Conference / Seminar
Suggestions
OpenMETU
Core
Inference of the Gaussian graphical model via the modifiedmaximum likelihood approach
Ağraz, Melih; Purutçuoğlu Gazi, Vilda (2017-01-04)
Inference of the Gaussian graphical model via the modi ed maximum likelihood approach
Purutçuoğlu Gazi, Vilda (null; 2017-06-01)
Inference of the JAK-STAT gene network via graphical models
Purutçuoğlu Gazi, Vilda; Weber, Gerhard William (null; 2011-06-01)
Inference of Biological Networks via Random Forest Algorithm
Purutçuoğlu Gazi, Vilda (2015-06-01)
Inference of Autoregressive Model with Stochastic Exogenous Variable Under Short-Tailed Symmetric Distributions
Bayrak, Ozlem Tuker; Akkaya, Ayşen (2018-12-01)
In classical autoregressive models, it is assumed that the disturbances are normally distributed and the exogenous variable is non-stochastic. However, in practice, short-tailed symmetric disturbances occur frequently and exogenous variable is actually stochastic. In this paper, estimation of the parameters in autoregressive models with stochastic exogenous variable and non-normal disturbances both having short-tailed symmetric distribution is considered. This is the first study in this area as known to the...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
V. Purutçuoğlu Gazi, “Inference of the biological systems via L1-penalized lasso regression,” presented at the 29th Meeting of Statisticians (01 Haziran 2013), Budapest, Macaristan, 2013, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/83372.