Kimberly Flagg Sellers

Foreword Special Issue on New Frontiers in Reliability and Risk Analysis: A Tribute to Nozer Darabsha Singpurwalla

Kundu, S., Mazzuchi, T., Sellers, K. F., & Soyer, R. (2025, January). APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Vol. 41.

Probability and Fuzzy Working in Concert-Honoring the Reliability Contributions of Nozer D. Singpurwalla

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 41(1).

On Non- and Weakly-Informative Priors for the Conway-Maxwell-Poisson (COM-Poisson) Distribution

(ArXiv Preprint No. 2311.18053).

Examining the Role of Quality of Institutionalized Healthcare on Maternal Mortality in the Dominican Republic

International Journal of Environmental Research and Public Health, 20(14), 6413.

The Conway–Maxwell–Poisson Distribution

A Flexible Mixed Model for Clustered Count Data

Stats, 5(1), 52–69.

A Recap of an ICSA 2021 Panel: Statistics and Data Science Partnerships and Collaborations across Sectors"

Gamerman, V., Kolassa, J., Li, J. Z., Natanegara, F., Sellers, K., Talwai, A., & Zou, K. H. (2022, February). Amstat News.

A Recap of an ICSA 2021 Panel: Statistics and Data Science Partnerships and Collaborations across Sectors"

Gamerman, V., Kolassa, J., Li, J. Z., Natanegara, F., Sellers, K., Talwai, A., & Zou, K. H. (2022, January). Amstat News.

A Flexible Multivariate Distribution for Correlated Count Data

Stats, 4(2), 308–326.

A flexible bivariate distribution for count data expressing data dispersion

Communications in Statistics - Theory and Methods, 52(13), 4692–4718.

A flexible regression model for zero- and<i>k</i>-inflated count data

Journal of Statistical Computation and Simulation, 91(9), 1815–1845.

A flexible univariate moving average time-series model for dispersed count data

Journal of Statistical Distributions and Applications, 8(1).

The JEDI Corner: How to Help Advocate for Justice, Equity, Diversity, and Inclusion"

Sellers, K. F. (2021, October). Amstat News.

A Conway–Maxwell-multinomial distribution for flexible modeling of clustered categorical data

Journal of Multivariate Analysis, 179, 104651.

A Flexible Univariate Autoregressive Time‐Series Model for Dispersed Count Data

Journal of Time Series Analysis.

Conway–Maxwell–Poisson</scp>regression models for dispersed count data

WIREs Computational Statistics, 13(6).

Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression

Journal of Statistical Computation and Simulation, 89(9), 1649–1673.

A flexible distribution class for count data

Journal of Statistical Distributions and Applications, 4(1).

Addressing Implicit Bias Among Women Statisticians and Data Scientists

CHANCE, 30(2), 38–41.

Bridging the Gap: A Generalized Stochastic Process for Count Data

The American Statistician, 71(1), 71–80.

Reply

The American Statistician, 71(2), 190–190.

Underdispersion models: Models that are “under the radar”

Underdispersion models: Models that are “under the radar.” Communications in Statistics - Theory and Methods, 46(24), 12075–12086.

A flexible zero-inflated model to address data dispersion

Computational Statistics & Data Analysis, 99, 68–80.

Bivariate Conway–Maxwell–Poisson distribution: Formulation, properties, and inference

Journal of Multivariate Analysis, 150, 152–168.

A Statistical Analysis of Weight Gain During the Freshman Year of College

Journal of Student Research, 4(1), 144–151.

Race Matters: Analyzing the Relationship between Colorectal Cancer Mortality Rates and Various Factors within Respective Racial Groups

Frontiers in Public Health, 2.

Surviving Graduate School: What Happens in Session, Stays in Session

CHANCE, 27(4), 23–25.

Data Dispersion: Now You See It… Now You Don't

Communications in Statistics - Theory and Methods, 42(17), 3134–3147.

Multidimensional Median Filters for Finding Bumps in Chemical Sensor Datasets

Journal of Sensor Technology, 02(01), 23–37.

Rejoinder: The COM‐Poisson Model for count data: A survey of methods and applications

Applied Stochastic Models in Business and Industry, 28(2), 128–129.

Statistical Analysis of Chemical Sensor Data

In W. Wang (Ed.), Advances in Chemical Sensors.

Statistical Analysis of Gel Electrophoresis Data

In S. Magdeldin (Ed.), Gel Electrophoresis - Principles and Basics.

A generalized statistical control chart for over‐ or under‐dispersed data

Quality and Reliability Engineering International, 28(1), 59–65.

The COM‐Poisson model for count data: a survey of methods and applications

Applied Stochastic Models in Business and Industry, 28(2), 104–116.

The effect of latency variables on repeated measures inference applied to the measurement of risk-taking as a function of psychopathy

Quality & Quantity, 47(1), 15–26.

A comparison of imputation procedures and statistical tests for the analysis of two-dimensional electrophoresis data

Proteome Science, 8(1), 66.

A flexible regression model for count data

The Annals of Applied Statistics, 4(2).

Feature Detection Techniques for Preprocessing Proteomic Data

International Journal of Biomedical Imaging, 2010(1), 1–9.

Modelling the effect of climate change on prevalence of malaria in western Africa

Statistica Neerlandica, 64(4), 388–400.

Characterization of Gene Expression Profiles of Normal Canine Retina and Brain Using a Retinal cDNA Microarray

In Advances in Experimental Medicine and Biology (pp. 179–184).

Many‐valued Logic in Multistate and Vague Stochastic Systems

International Statistical Review, 76(2), 247–267.

Identification of High-Risk Patients Among Those Diagnosed With Thin Cutaneous Melanomas

Journal of Clinical Oncology, 25(9), 1129–1134.

Incidence and prevalence of abnormal liver associated enzymes in patients with atrial fibrillation in a routine clinical care population

Pharmacoepidemiology and Drug Safety, 17(1), 43–51.

Innate Immunity Modulates Adipokines in Humans

The Journal of Clinical Endocrinology & Metabolism, 92(6), 2272–2279.

Lights, Camera, Action! Systematic variation in 2‐D difference gel electrophoresis images

ELECTROPHORESIS, 28(18), 3324–3332.

4. Bayesian Methods

Fuzzy Logic and Probability Applications, pp. 73–86.

5. Considerations for Using Fuzzy Set Theory and Probability Theory

In T. J. Ross, J. M. Booker, & W. J. Parkinson (Eds.), Fuzzy Logic and Probability Applications (pp. 87–104).

Linking Probability Theory and Fuzzy Sets: A Study in Uncertainty Assessment

43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference.

A definition of vague coherent systems

Contemporary Mathematics, pp. 43–51.