publications

Publications

Submitted/being revised

W. Du, J. Hannig, T. C. M. Lee, Y. Su, and C. Zhang, AutoGFI: Automated Generalized Fiducial Inference for Regularized Additive Noise Problems, under revision.

J. Fu, J. Prothero and J. Hannig, Algorithm for detection of illegal discounting in North Carolina Education Lottery.

J. Prothero, M. Jiang, J. Hannig, Q. Tran-Dinh, A. Ackerman, J.S. Marron, Data Integration Via Analysis of Subspaces (DIVAS),

A. C. Murph, J. Hannig, J. P. Williams, Generalized Fiducial Inference on Differentiable Manifolds.

Y. Liu, J. Hannig and A. C. Murph, A Geometric Perspective on Bayesian and Generalized Fiducial Inference

Y. Cui and J. Hannig, Demystifying Inferential Models: A Fiducial Perspective

X. Yang, J. Hannig, K.A. Hoadley, I. Carmichael and J.S. Marron, Measure of Strength of Evidence for Visually Observed Differences between Subpopulations.

In Press

A. Murph, J. Hannig, J.P. Williams, Introduction to Generalized Fiducial Inference, to appear in Handbook on Bayesian, Fiducial and Frequentist (BFF) Inferences, accepted October 2021.

Y. Cui and J. Hannig, M.R. Kosorok, A unified fiducial approach to interval-censored data, to appear in Journal of the American Statistical Association, accepted in August 2023. https://arxiv.org/abs/2111.14061

S. Lu and J. Hannig, Gender Wage Gap Of Assistant Professors in US Public Universities, to appear in Journal of Young Investigators, accepted in April 2023.

Y. Cui and J. Hannig. A fiducial approach to nonparametric deconvolution problem:
discrete case, to appear in Science China Mathematics, accepted in January 2023. doi:10.1007/s11425-021-2086-5

2023

Y. Cui, R. Gong, J. Hannig and K. Hoffman (2023), Technical Comment on “Policy impacts of statistical uncertainty and privacy”, Science, 380, eadf9724. doi:10.1126/science.adf9724

J. B. Prothero, J. Hannig and J.S. Marron (2023), New Perspective on Centering, The New England Journal of Statistics in Data Science, pp. 1-21. doi:10.51387/23- NEJSDS31

J. P. Williams, Y. Xie, J. Hannig (2023), The EAS approach for graphical selection consistency in vector autoregression models, Canadian Journal of Statistics, 51, pp. 674 –703. doi:10.1002/cjs.11726

J. P. Williams, D. M. Ommen and J. Hannig (2023) Generalized fiducial factor: an alternative to the Bayes factor for forensic identification of source problems, Annals of Applied Statistics, 17, pp. 378-402. doi:10.1214/22-AOAS1632

X. Yang, K.A. Hoadley, J. Hannig, J.S. Marron (2023), Jackstraw Inference for AJIVE Data Integration, Computational Statistics and Data Analysis, 180, 107649. doi:10.1016/j.csda.2022.107649

2022

E.L. Boone, J. Hannig, R. Ghanam, S. Ghosh, F. Ruggeri and S. Prudhomme (2022), Model validation of a single degree-of-freedom oscillator: a case study, Stats, 5, pp. 1195-1212. doi:10.3390/stats5040071

Y. Su, J. Hannig, T.C.M. Lee (2022), Uncertainty Quantification in Graphon Estimation using Generalized Fiducial Inference, IEEE Transactions on Signal and Information Processing over Networks, 8, pp. 597-609. doi:10.1109/TSIPN.2022.3188458

T. Petty, J. Hannig, T. I. Huszar, H. Iyer (2022), A New String Edit Distance and Applications, Algorithms, 15, 242. doi:10.3390/a15070242

S. Wu, J. Hannig, T.C.M. Lee, Uncertainty Quantification for Honest Regression
Trees, Computational Statistics and Data Analysis, 30, pp. 934-945. doi:10.1080/10618600.2021.1923514

J. Hannig and H. Iyer, Testing For Calibration Discrepancy of Reported Likelihood
Ratios in Forensic Science, Journal of the Royal Statistical Society: Series
A (Statistics in Society), 185, pp. 267-301. doi:10.1111/rssa.12747

2021

Randy C. S. Lai, J. Hannig and Thomas C. M. Lee (2021), Method G: Uncertainty Quantification for Distributed Data Problems using Generalized Fiducial Inference, Journal of Computational and Graphical Statistics, 30, pp. 934-945. doi:10.1080/10618600.2021.1923514

I. Carmichael, B. C. Calhoun, K. A. Hoadley, M. A. Troester, J. Geradts, H. D.
Couture, L. Olsson, C. M. Perou, M. Niethammer, J. Hannig and J.S. Marron, (2021)Joint
and individual analysis of breast cancer histologic images and genomic covariates, Annals of Applied Statistics, 15, pp. 1697-1722. doi:10.1214/20-AOAS1433

W. J. Shi, J. Hannig, R. C. S. Lai, T. C. M. Lee (2021), Covariance estimation via fiducial inference, Statistical Theory and Related Fields, 4, pp. 316-331. doi:10.1080/24754269.2021.1877950

W, Li, J. Hannig and C. D. Jones (2021), A Note on Optimal Sampling Strategy for
Structural Variant Detection Using Optical Mapping, Communications in Statistics,
50, pp. 4763-4777. doi:10.1080/03610926.2020.1723638

W. Li, J. Hannig and S. Mukherjee (2021), Subspace Clustering through Sub-Clusters,Journal of Machine Learning Research, 22, 53.

S. Wu, J. Hannig, T.C.M. Lee (2021), Uncertainty Quantification for Sparse High
Dimensional Principal Component Regression, Electronic Journal of Statistics, 15,
pp. 2157-2178. doi:10.1214/21-EJS1837

S. D. Neupert, C. M. Growney, X. Zhu, J. K. Sorensen, E. L. Smith and J. Hannig
(2021), BFF: Bayesian, Fiducial, and Frequentist Analysis of Cognitive Engagement
among Cognitively Impaired Older Adults, Entropy, 23, 428. doi:10.3390/e23040428

Y. Zou, J. Hannig and D. S Young (2021), Generalized fiducial inference on the
mean of zero-inflated Poisson and Poisson hurdle models, Journal of Statistical Distributions and Applications, 8, 5. doi:10.1186/s40488-021-00117-0

K. Hoffman, J. Hannig and K. Zhang (2021), Comments on “A Gibbs sampler for a class of random convex polytopes”, Journal of the American Statistical Association, 116, pp. 1206-1210. doi:10.1080/01621459.2021.1950002

2020

G. Li and J. Hannig (2020), Deep fiducial inference, STAT, 9, e308. doi:10.1002/sta4.308

J.P. Williams, C.B. Storlie, T. M. Therneau, C. R. Jack Jr. and J. Hannig (2020), A Bayesian Approach to Multi-State Hidden Markov Models: Application to Dementia Progression, Journal of American statistical Association, 115, pp. 16-31, doi:10.1080/01621459.2019.1594831

S.D. Neupert and J. Hannig (2020), BFF: Bayesian, Fiducial, Frequentist Analysis of Age Effects in Daily Diary Data, Journal of Gerontology: Psychological Sciences, 75, pp. 67-79 doi:10.1093/geronb/gbz100

2019

Y. Cui and J. Hannig (2019), Nonparametric generalized fiducial inference for survival functions under censoring with discussion and rejoinder by the authors, Biometrika, 106, pp. 501-51. doi:10.1093/biomet/asz016

Y. Liu, J. Hannig and A. Pal Majumder (2019), Second-Order Probability Matching Priors for the Person Parameter in Unidimensional IRT Models, Psychometrika, 84, pp. 701-718. doi:10.1007/s11336-019-09675-4

K. Hindberg, J. Hannig, F. Godtliebsen (2019), A novel scale-space approach for multinormality testing and the k-sample problem in the high dimension low sample size scenario. PLoS ONE, 14(1): e0211044A. doi:10.1371/journal.pone.0211044

J. P. Williams and J. Hannig (2019), Non-penalized variable selection in high- dimensional linear model settings via generalized fiducial inference, Annals of Statistics, 47, pp. 1723-1753. doi:10.1214/18-AOS1733

S. Almada Monter, A. Budhiraja, and J. Hannig (2018), Source detection algorithms for dynamic contaminants based on the analysis of a hydrodynamic limit, SIAM Journal Applied Math, 78, pp. 2279-2625. doi:10.1137/15M1044497

J. Hannig (2019), Discussion of ”Prior-based Bayesian Information Criterion (PBIC)” by Bayarri et al, Statistical Theory and Related Fields, 3, pp. 30-31. doi:10.1080/24754269.2019.1611144

J. Hannig, S. Riman, H. Iyer and P. M. Vallone (2019), Are Reported Likelihood Ra- tios Well Calibrated? Forensic Science International: Genetics Supplement Series, 7, pp. 572-574 (extended abstract). doi:10.1016/j.fsigss.2019.10.094

2018

Q. Feng, J. Hannig, M. Jiang and J. S. Marron (2018), Angle-Based Joint and Individual Variation Explained, Journal of Multivariate Analysis, 166, pp. 241-265.

J. Hannig, Q. Feng, H. Iyer, J. Wang, X. Liu (2018), Fusion learning for Inter-laboratory Comparisons, Journal of Statistical Planning and Inference, 195, pp. 64-79.

2017

Y. Liu and J. Hannig (2017), Generalized fiducial inference for logistic graded response models, Psychometrika. 82, pp. 1097-1125.

J. Hannig, (2017) Discussion of "Beyond objective and subjective in statistics?" by Gelman and Hennig, Journal of Royal Statistical Society Ser. B, 180. p. 1009.

2016

L. Liao, C. Park, J. Hannig, K.-H. Kang (2016), Autocovariance Function Estimation via Penalized Regression, Journal of Computational and Graphical Statistics, 25, pp. 1041-1056. with supplementary document.

J. Hannig, H. Iyer, R. C. S. Lai and T. C. M. Lee (2016), Generalized Fiducial Inference: A Reviev and New Results, Journal of American Statistical Association, 111, pp. 1346-1361 with supplementary document.

C. Liu, X. Xu and J. Hannig (2016), Least squares generalized inferences in unbalanced two-component normal mixed linear model, Computational Statistics, 31, pp. 973- 988.

Y. Liu and J. Hannig (2016), Generalized Fiducial Inference for Binary Logistic Item Response Models, Psychometrika, 81, pp. 290-324.

P. Borysov, J. Hannig, J.S. Marron, E. Muratov, D. Fourches and A. Tropsha (2016), Activity Prediction and Identification of Mis-annotated Chemical Compounds Using Extreme Descriptors, Chemometrics, 30, pp. 99 – 108.

Q. Feng, J. Hannig, J.S. Marron (2016), A Note on Automatic Data Transformation, STAT, 5, pp. 82 – 87.

2015

M. Heller, J. Hannig, M. R. Leadbetter (2015), Optimal sample planning for system state analysis with partial data collection, STAT, 4, pp. 69 – 80.

R. C. S. Lai, J. Hannig and T. C. M. Lee (2015), Generalized Fiducial Inference for Ultrahigh Dimensional Regression, Journal of American Statistical Association, 110, pp. 760 – 772

S. Bhamidi, J. Hannig, C. Y. Lee and J. Nolen (2015), The importance sampling technique for understanding rare events in Erdos-Renyi random graphs, Electronic Journal of Probability, 20, Article 107, pp. 1–30.

2014

J. Hannig (2014), Discussion of ``On the Birnbaum Argument for the Strong Likelihood Principle'' by D. G. Mayo, Statistical Science, 29, pp. 254 --258.

P. Borysov, J. Hannig, J. S. Marron (2014), Asymptotics of Hierarchical Clustering for Growing Dimension Journal of Multivariate Analysis, 124, pp. 465 – 479.

C. Park, J. Hannig and K-H. Kang (2014), Nonparametric Comparison of Multiple Regression Curves in Scale-Space Journal of Computational and Graphical Statistics, 23, pp. 657 -- 677.

D. L. Sonderegger and J. Hannig (2014), Fiducial theory for free-knot spline in Contemporary Developments in Statistical Theory, a Festschrift in honor of Professor Hira L. Koul, Springer, pp. 155 – 189. with an on-line appendix.

J. Hannig, R. C. S. Lai and T. C. M. Lee (2014), Computational Issues of Generalized Fiducial Inference, Computational Statistics and Data Analysis special issue on Imprecision in Statistical Data Analysis, 71, pp. 849 – 858.

2013

Y. Zhang, E. K. P. Chong, J. Hannig and D. Estep (2013), On Continuum Limits of Markov Chains with Applications to Network Modeling, IEEE Access, 1, pp. 577--595.

Y. Zhang, E. K. P. Chong, J. Hannig and D. Estep (2013), Continuum Modeling and Control of Large Nonuniform Wireless Networks via Nonlinear Partial Differential Equations, Abstract and Applied Analysis, special issue on Advances in Nonlinear Complexity Analysis for Partial Differential Equations, Article ID 262581, 16 pages.

J. Hannig (2013) Generalized Fiducial Inference via Discretizations, Statistica Sinica, 23, pp. 489-514.

N. Burch, E. K. P. Chong, D. Estep and J. Hannig (2013) Analysis of Routing Protocols and Interference-limited Communication in Large Wireless Networks via Continuum Modeling, Journal of Engineering Mathematics, 79, pp. 183-199.

J. Hannig, T. C. M Lee and C. Park (2012), Metrics for SiZer Map Comparison, Stat, 2, pp. 49-60, with Matlab code.

2012

J. Cisewski and J. Hannig (2012) Generalized Fiducial Inference for Normal Linear Mixed Models, Annals of Statistics, 40, pp. 2102 - 2127, with supplementary material and Matlab code.

J. Hannig and Min-ge Xie (2012), A note on Dempster-Shafer Recombinations of Confidence Distributions, Electronic Journal of Statistics, 6, pp. 1943-1966.

J. Cisewski, E. Snyder, J. Hannig and L. Oudejans (2012), Support vector machine classification of suspect powders using laser induced breakdown spectroscopy (LIBS) spectral data, Journal of Chemometrics, 26, pp. 143 -- 149.

C. M. Wang, J. Hannig and H. K. Iyer (2012), Pivotal methods in the propagation of distributions, Metrologia, 49, pp. 382 -- 389.

C. M. Wang, J. Hannig and H. K. Iyer (2012), Fiducial Prediction Intervals, Journal of Statistical Planning and Inference, 142, pp. 1980 -- 1990.

D. Wandler and J. Hannig (2012) Generalized Fiducial Confidence Intervals for Extremes, Extremes, 15, pp. 67 -- 87. R code: known threshold, unknown threshold.

D. Wandler and J. Hannig (2012) A Fiducial Approach to Multiple Comparisons, Journal of Statistical Planning and Inference, 142, pp 878 -- 895.

2011

D. Wandler and J. Hannig (2011), Fiducial Inference on the largest mean of a Multivariate Normal Distribution, Journal of Multivariate Analysis, 102, pp. 87 – 104.

C. B. Storlie, J. Hannig and T. C. M. Lee (2011), Statistical consistency of the data association problem in multiple target tracking, Electronic Journal of Statistics, 5, 1227 -- 1275..

2010

C. Park, T. C. M. Lee and J. Hannig (2010), Multiscale Exploratory Analysis of Regression Quantiles using Quantile SiZer, Journal of Computational and Graphical Statistics, 19, pp. 497 – 513 with suplementary documents.

J. Hannig, H. Iyer and T. C. M. Lee (2010), Fiducial Inference and Generalizations, in International Encyclopedia of Statistical Science, Springer.

P. J. Brockwell and J. Hannig (2010), CARMA(p,q) Generalized Random Processes, Journal of Statistical Planning and Inference, 140, pp. 3613 – 3618.

S. S. Lee and J. Hannig (2010), Detecting jumps from levy jump diffusion processes, Journal of Financial Economics, 96, pp. 271-290.

2009

J. Hannig (2009), On Generalized Fiducial Inference, Statistica Sinica, 19, 491-544.

J. Hannig and T. C. M. Lee (2009), Generalized Fiducial Inference for Wavelet Regression, Biometrika, 96, pp. 847 – 860 Suplementary Document.

C. Park, J. Hannig and K.-H. Kang (2009), Improved SiZer for Time Series, Statistica Sinica, 19, pp. 1511 - 1530.

C. Park, A. Vaughan, J. Hannig and K.-H. Kang (2009), SiZer Analysis for Comparison of Two Time Series, Journal of Statistical Planning and Inference, 139, pp. 3974 - 3988.

C. B. Storlie, T. C. M. Lee, J. Hannig and D. Nychka (2009), Tracking of multiple merging and splitting targets; a statistical perspective with discussion and rejoinder by the authors, Statistica Sinica, 19, pp. 1 - 52.

2008

L. E, J. Hannig and H. Iyer (2008), Fiducial Intervals for Variance Components in an Unbalanced Two-component Normal Mixed Linear Model, Journal of American Statistical Association, 103, pp. 854 - 865.

E. K. P. Chong, D. Estep and J. Hannig (2008), Continuum Modeling of Large Networks, International Journal of Numerical Modeling: Electronic Networks, Devices, and Fields, 21, pp. 169 -- 186.

H. Li, P. R. Barbosa, E. K. P. Chong, J. Hannig and S. R. Kulkarni (2008) Zero-Error Target Tracking with Limited Communication, IEEE Journal on Selected Areas in Communications, Special Issue on Control and Communications, 26, pp. 686 - 694.

2007

J. Hannig, H. K. Iyer and C.M. Wang (2007), Fiducial Approach to Uncertainty Assessment Accounting for Error due to Instrument Resolution, Metrologia, 44, pp. 476 - 483.

2006

J. Hannig, H. K. Iyer and P. Patterson (2006), Fiducial Generalized Confidence Intervals, Journal of American Statistical Association, 101, pp. 254-269.

J. Hannig and J. S. Marron (2006), Advanced Distribution Theory for SiZer, Journal of American Statistical Association, 101, pp. 484-499.

J. Hannig,E. K. P. Chong and S. R. Kulkarni (2006), Relative Frequencies of Generalized Simulated Annealing, Math. of OR., 31, pp. 199-215.

J. Hannig and T. C. M. Lee (2006), Robust SiZer for Exploration of Regression Structures and Outlier Detection, Journal of Computational and Graphical Statistics, 15, pp. 101-117.

J. Hannig, L. E, A. Abdel-Karim and H. K. Iyer (2006), Simultaneous Fiducial Generalized Confidence Intervals for Ratios of Means of Lognormal Distributions, Austrian Journal of Statistics, 35, pp. 261-269.

J. Hannig (2006), Asymptotic Bounds for Coverage Probabilities for a Class of Confidence Intervals for the Ratio of Means in a Bivariate Normal Distribution, Journal of Probability and Statistical Science, 4, pp. 41-49.

J. Hannig and T. C. M. Lee (2006), Smoothing of the Poisson signal under L_2 and Kullback-Leibler Discrepency, Journal of Statistical Planning and Inference, 136, pp. 882-908 (includes a small correction to one of the proofs)

2004

F. Gao, J. Hannig, T.-Y. Lee and F. Torcaso (2004), Exact $L^2$ small balls of Gaussian processes, J. of Theoretical Probability, 17, pp. 503-520.

J. Hannig and T. C. M. Lee (2004), Kernel Smoothing of Periodograms under Kullback-Leibler Discrepancy, Signal Processing, 84, pp. 1255-1266.

2003

F. Gao, J. Hannig and F. Torcaso (2003), Integrated Brownian motions and Exact L2-small balls, Annals of Probability, 31, pp. 1320-1337.

F. Gao, J. Hannig, T.-Y. Lee and F. Torcaso (2003), Laplace transforms via Hadamard Factorization, Electronic J. of Probability, 8, paper no. 13, pp. 1-20.

F. Gao, J. Hannig and F. Torcaso (2003), Comparison Theorems for Small Deviations of Random Series, Electronic J. of Probability, 8, paper no. 21, pp. 1-17.

J. Hannig, C. M. Wang and H. K. Iyer (2003), Uncertainty calculation for the ratio of dependent measurements, Metrologia, 40, pp. 177-183.

J. Hannig (2003), On filtrations related to purely discontinuous martingales, Seminaire de Probabilites XXXVI, Lecture Notes in Mathematics 1801, pp. 360-365.

J. Hannig, J. S. Marron, G. Samorodniztky and F. D. Smith (2003), Log-normal durations can give long range dependence, Mathematical Statistics and Applications: Festschrift for Constance van Eeden, IMS Lecture Notes-- Monograph Series 42, pp. 333-344.

2001

J. Hannig, J.S. Marron and R.H. Riedi (2001), Zooming statistics: Inference across scales, J. Korean Stat. Soc., 30, pp. 327-345.

2000

J. Hannig, On purely discontinuous martingales, Ph.D. dissertation, Michigan State University, East Lansing, MI

Never Published

L. E, J. Hannig and H. K. Iyer. Fiducial Generalized Confidence Interval for Median Lethal Dose (LD50), with suplementary document.

J. Hannig and D. Katsoridas, Generalized Fiducial Inference for High Frequency Data in the Presence of Microstructure Noise.

A. Pal Majumder, Y. Liu and J. Hannig, Higher order asymptotics of Generalized Fiducial Distribution.

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