Publications 📚

Selected publications in

A) Diagnostic Methods, Classical and Robust Regression Modelling, Multicollinearity

• Yuksel, G., Billor, N., and Unal, D. (2010), "Shrinkage Pre-test Estimator of the Univariate Normal Mean," Pakistan Journal of Statistics, 26, 3, 461 - 477.

• Arslan, O. and Billor, N. (2000), "Robust Liu Estimator for Regression Based on M-estimator," Journal of Applied Statistics, 27, 39 - 47.

• Billor, N. and Loynes, R. M. (1993), "Local Infuence: A New Approach," Communications in Statistics Theory and Methods, Vol 22, No.6, 1595 - 1611.

B) Outlier Detection and Multivariate Data Analysis

• Shi, R., Billor, N., and Ceyhan, E. (2024), ”Outlier Detection with Cluster Catch Digraphs,” https://arxiv.org/abs/2409.11596. Submitted, Pre-print.

• Nnyaba,U., Shemtaga, H. , Collins, D. W.,. Muyskens, A. L.. Priest, B. E., and Billor, N. (2024), “Enhancing Electrocardiography Data Classification Confidence: A Robust Gaussian Process Approach (MuyGPs)“, https://arxiv.org/abs/2409.04642, Submitted, Pre-print.

•  Yi, Y. . Billor, N., Ekstrom, A., and Zheng, J. (2023) ”CW-ICA: An Efficient Dimensionality Determination Method for Independent Component Analysis,” Scientific Reports, 14, 143, https://doi.org/10.1038/s41598-023-49355-z.

• Magnotti, J. and Billor, N. (2014), "Finding multivariate outliers in fMRI time-series data," Computers and Biology in Medicine, 53, 115-124. (Honorable Mention Paper, Top 10% ).

• Bell, R. C., Jones-Farmer, L. A. and Billor, N. (2013), "A Distribution-Free Control Chart for Retrospective Location Analysis of Subgrouped Multivariate Data," Technometrics, DOI:10.1080/00401706.2013.879264.

• Turkmen, A. and Billor, N. (2012), "Partial Least Squares Classification for High Dimensional Data Using the PCOUT Algorithm," Computational Statistics, 28, 2, Page 771-788.

• Billor, N. , Abebe, A., Turkmen, A. and Nudurapati, S. (2008), "Classification based on Data Depth," Journal of Classification, 25, 249 - 260.

• Caroni, C. and Billor, N., (2007), "Robust Detection of Multiple Outliers in Grouped Multivariate Data," Journal of Applied Statistics, 34, 19, 1241 - 1250.

• Billor, N., Hadi, A. S., and Velleman, P. F. (2000), "BACON: Blocked Adaptive Computationally-Efficient Outlier Nominators," Computational Statistics and Data Analysis, 34, 279 - 298.

C) Functional Data Analysis

• Yuan, Y. and Billor N. (2024) ”SURE Independent Screening for Functional Regression Model,” Communication in Statistics- Simulation and Computation, https://doi.org/10.1080/03610918.2024.2325567.

•  Yi, Y., Billor N., Liang, M. , Cao, X., Ekstrom, A. , and Zheng, J.(2022) ”Classification of EEG signals: An interpretable approach using functional data analysis,” Journal of Neuroscience Methods, Volume 376, https://doi.org/10.1016/j.jneumeth.2022.109609.

• Lima, I. R., Cao, G. and Billor, N. (2019) "M-Based Simultaneous Inference for the Mean Function of Functional Data," Annals of the Institute of Statistical Mathematics, DOI 10.1007/s10463-018-0656-y.

• Pannu, J. and Billor, N. (2015) "Robust Group-Lasso for Functional Regression Model," Communications in Statistics: Simulations and Computation, DOI:10.1080/03610918.2015.1096375.

• Denhere, M. and Billor, N. (2013), "Robust Principal Component Functional Logistic Regression," Communications in Statistics: Simulations and Computation, DOI: 10.1080/03610918.2013.861628.

• Lee, S., Shin, H., and Billor, N. (2013), "M-type Smoothing Spline Estimation for Principal Functions," Computational Statistics and Data Analysis, 66, 89 - 100.

• Sawant, P., Billor, N., and Shin, H. (2012), "Robust Functional Principal Component Analysis," Computational Statistics, 27, 1, 83 - 102.

D) Genomewide Association

• Turkmen, A.S., Yuan, Y. and Billor N. (2019) ”Evaluation of Methods for Adjusting Population Stratification in Genome-wide Association Studies: Standard versus Categorical Principal Component Analysis,” Annals of Human Genetics, https://www.ncbi.nlm.nih.gov/pubmed/31322288.

E) Interdisciplinary Collaborative Study

• Zheng, J., Li, Y. , Billor, N., Ahmed, M. I., Fang, Y. D., Pat, B. , Denney, T. S., Dell’Italia, L. J. (2023) ”Understanding Post-Surgical Decline in Left Ventricular Function in Primary Mitral Regurgitation using Regression and Machine Learning Models,” Frontiers in Cardiovascilur Medicine,Volume 10, https://doi.org/10.3389/fcvm.2023.1112797.

• Tanni, K. A., Billor, N., Ngorsuraches, S. Westrick, Xu, P., Johnson, B., and Qian,J. (2024), ”RWD57 Trends and Factors Affecting the Initiation of Denosumab and Zoledronic Acid among Patients with Metastatic Lung, Breast, and Prostate Cancer in the United States,” Value in Health, 27, (6), S367-S368 https://doi:10.1016/j.jval.2024.03.1711.

• Billor, N. and Turkmen, A.S. (2019) ”Emerging Statistical Methodologies in Twenty-First Century,” Invited paper to Women in Industrial and Systems Engineering: Key Advances and Perspectives on Emerging Topics, Springer, https://www.springer.com/gp/book/9783030118655.

• Acquah, G., Via, B. ,Fasina, O., Adhikari, S., Billor, N. and Eckhardt, L. (2018) "Estimating the Basic Density and Mechanical Properties of Elite Loblolly Pine Families with Near Infrared Spectroscopy," Forest Science, doi.org/10.1093/forsci/fxx009.