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Ivor Cribben

Associate Professor, Department of Accounting and Business Analytics
Curriculum Vitæ
Contact Overview Announcements Courses Publications

Contact

Associate Professor, Department of Accounting and Business Analytics
Email
cribben@ualberta.ca
Phone
(780) 248-1930
Address
4-30G Business Building
11203 Saskatchewan Drive NW
Edmonton AB
T6G 2R6

Overview

About

Google Scholar

Research

Research Interests

  • Time Series Analysis
  • Statistical Methods in fMRI
  • Methods for High Dimensional Data
  • Graphical Models
  • Non-Parametric Statistics
  • Extreme Value Theory
  • Neuroeconomics
Teaching

Teaching Interests

  • Forecasting for Planners and Managers
  • Applied Business Analysis of Time Series and Panel Data
  • Multivariate Data Analysis

Announcements

A Spotlight on Research at the Alberta School of Business

How is neuro statistics linked with decision-making?

My findings tell us...

  • The brain's functionality and dynamic integration can be statistically analyzed by looking at networks.
  • Statistical analysis of fMRI scans shows that people with gambling disorders have unique brain networks as they are making financial decisions.
  • The comparison of networks can be further applied to a broad spectrum of brain disorders such as dyslexia, cerebral palsy and Alzheimer's. 

Read more about this research...

Courses

OM 710 - Individual Research

Winter Term 2021

Browse more courses taught by Ivor Cribben

Publications

Do NHL goalies get hot in the playoffs? A multilevel logistic regression analysis
Author(s): Ding, L., Cribben, I., Ingolfsson, A., Tran, M.
Publication Date: 2/19/2021
Publication: arxiv
Page Numbers: 1-19
External Link: https://arxiv.org/abs/2102.09689
Cross-covariance isolate detect: a new change-point method for estimating dynamic functional connectivity
Author(s): Anastasiou, A., Cribben, I., & Fryzlewicz, P.
Publication Date: 12/20/2020
Publication: bioRxiv
Page Numbers: 1-52
External Link: https://www.biorxiv.org/content/biorxiv/early/2020/12/22/2020.12.20.423696.full.pdf
Nonparametric Anomaly Detection on Time Series of Graphs
Author(s): Ofori-Boateng, D., Gel, Y., Cribben, I.
Publication Date: 10/14/2020
Publication: Journal of Computational and Graphical Statistics
Page Numbers: 1-12
External Link: https://www.tandfonline.com/doi/full/10.1080/10618600.2020.1844214
Generalized reliability based on distances
Author(s): Xu, M., Reiss, P.T., Cribben, I.
Publication Date: 4/27/2020
Publication: Biometrics
Page Numbers: 1-13
External Link: https://onlinelibrary.wiley.com/doi/full/10.1111/biom.13287
After the Fort McMurray wildfire there are significant increases in mental health symptoms in grade 7–12 students compared to controls
Author(s): Brown, M.R.G., Agyapong, V., Greenshaw, A.J., Cribben, I.
Publication Date: 12/27/2018
Publication: BMC Psychiatry
Volume: 19
Issue: 1
Page Numbers: 1-11
External Link: https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-018-2007-1
Change points in heavy‐tailed multivariate time series: Methods using precision matrices
Author(s): Cribben, I.
Publication Date: 8/16/2018
Publication: Applied Stochastic Models in Business and Industry
Volume: 35
Issue: 2
Page Numbers: 299-320
External Link: https://onlinelibrary.wiley.com/doi/full/10.1002/asmb.2373
A longitudinal model for functional connectivity networks using resting-state fMRI
Author(s): Hart, B., Cribben, I., Fiecas, M.
Publication Date: 5/30/2018
Publication: NeuroImage
Volume: 178
Page Numbers: 687-701
External Link: https://www.sciencedirect.com/science/article/pii/S105381191830497X
A clustering-based feature selection method for automatically generated relational attributes
Author(s): Rezaei, M., Cribben, I., Samorani, M.
Publication Date: 4/5/2018
Publication: Annals of Operations Research
Page Numbers: 1-31
External Link: https://link.springer.com/article/10.1007/s10479-018-2830-2
Sparse graphical models for functional connectivity networks: best methods and the autocorrelation issue
Author(s): Zhu, Y., Cribben, I.
Publication Date: 4/1/2018
Publication: Brain Connectivity
Volume: 8
Issue: 3
Page Numbers: 139-165
External Link: https://www.liebertpub.com/doi/full/10.1089/brain.2017.0511
Estimating whole‐brain dynamics by using spectral clustering
Author(s): Cribben, I., Yu, Y.
Publication Date: 2017
Publication: Journal of the Royal Statistical Society: Series C (Applied Statistics)
Volume: 66
Issue: 3
Page Numbers: 607-627
External Link: https://rss.onlinelibrary.wiley.com/doi/full/10.1111/rssc.12169
extremogram: estimating extreme value dependence
Author(s): Frolova, N, Cribben, I.
Publication Date: 2016
External Link: https://cran.r-project.org/web/packages/extremogram/index.html
Detecting functional connectivity change points for single-subject fMRI data
Author(s): Cribben, I., Wager, T.D., Lindquist, M.A.
Publication Date: 2013
Publication: Frontiers in Computational Neuroscience
Volume: 7:143
External Link: http://www.frontiersin.org/Journal/10.3389/fncom.2013.00143/abstract
Dynamic Connectivity Regression: Determining state-related changes in brain connectivity
Author(s): Cribben, I., Haraldsdottir, R., Atlas, L., Wager, T.D., Lindquist, M.A.
Publication Date: 2012
Publication: NeuroImage
Volume: 61
Page Numbers: 907 - 920
External Link: http://www.sciencedirect.com/science/article/pii/S1053811912003515
Towards Estimating Extremal Serial Dependence via the Bootstrapped Extremogram
Author(s): Davis, R.A., Mikosch, T., Cribben, I
Publication Date: 2012
Publication: Journal of Econometrics
Volume: 170
Page Numbers: 142 - 152
External Link: http://dx.doi.org/10.1016/j.jeconom.2012.04.003