Jennifer Hoeting: Book, selected papers and other work

Click here for most up-to-date publication list (my cv)

Areas:

Book: Computational Statistics
Model Selection and Model Averaging
Spatial Statistics
Statistical Methods and Models
Applications

Book

Computational Statistics by Geof H. Givens and Jennifer A. Hoeting

Wiley, 2005

A comprehensive text on modern and classical methods of statistical computing and computational statistics with detailed examples and problems drawn from diverse fields including bioinformatics, ecology, medicine, computer vision, and stochastic finance. R code available on book website.

Model Selection and Model Averaging

Model Selection for Geostatistical Models
Authors: Jennifer A. Hoeting, Richard A. Davis, Andrew A. Merton, Sandra E. Thomspon.
Ecological Applications (2006), 16:1, 87-98

Bayesian Model Averaging: A Tutorial
Authors: Jennifer A. Hoeting, David Madigan, Adrian Raftery, Chris T. Volinsky
Statistical Science (1999) 14:4, 382-417.

Bayesian Model Averaging for Linear Regression Models
Authors: Adrian E. Raftery, David Madigan, and Jennifer A. Hoeting
Journal of the American Statistical Association, 1997, v. 92, 179-191.

Bayesian Predictive Simultaneous Variable and Transformation Selection in the Linear Model
Authors: Jennifer A. Hoeting and Joseph G. Ibrahim
A revised version appeared in Computational Statistics and Data Analysis, 1998, v. 28, 87-103.
CSDA homepage

Bayesian Variable and Transformation Selection in Linear Regression
Authors: Jennifer Hoeting, Adrian E. Raftery and David Madigan
Journal of Computational and Graphical Statistics,(2002) 11:3, 485-507.

A Method for Simultaneous Variable Selection and Outlier Identification in Linear Regression
Authors: Jennifer Hoeting, Adrian E. Raftery and David Madigan
A revised version appeared in Computational Statistics and Data Analysis, (1996),22, 251-270.
CSDA homepage

Methodology for Bayesian Model Averaging: An Update
Authors: Jennifer A. Hoeting
Proceedings - Manuscripts of invited paper presentations, International Biometric Conference, Freiburg, Germany, 2002, 231-240.

Bayesian Model Averaging
Authors: David Madigan, Adrian E. Raftery, Chris Volinsky, Jennifer Hoeting
A revised version appeared in Integrating Multiple Learned Models (IMLM-96), P. Chan, S. Stolofo, and D. Wolpert (Eds.), 1996

Spatial Statistics

A Clipped Latent-Variable Model for Spatially Correlated Ordered Categorical Data
Authors: M. D. Higgs and J. A. Hoeting (2010)
To appear in Computational Statistics and Data Analysis, DOI 10.1016/j.csda.2010.02.024

Spatial Designs and Properties of Spatial Correlation: Effects on Covariance Estimation
Authors: K. Irvine, A. I. Gitelman, and J. A. Hoeting
Journal of Agricultural, Biological and Environmental Statistics (2007),12:4,450-469.
JABES homepage

Model Selection for Geostatistical Models
Authors: J. A. Hoeting, R. A. Davis, A. A. Merton, S. E. Thomspon.
Ecological Applications (2006), 16:1, 87-98

Some Perspectives on Modeling Species Distributions
Discussion of article by A. E. Gelfand, J. A. Silander, S. Wu, A. Latimer, P. O. Lewis, A. G. Rebelo, M. Holder
Author: Jennifer A. Hoeting
Bayesian Analysis, 2006, 1:1, 93-98.

Factors Affecting Species Distribution Predictions: A Simulation Modeling Experiment
Authors: G. C. Reese, K. R. Wilson, J. A. Hoeting, C. H. Flather
Ecological Applications, 2005

An Improved Model for Spatially Correlated Binary Responses
Authors: Jennifer A. Hoeting, Molly Leecaster, David Bowden
Journal of Agricultural, Biological and Environmental Statistics (2000) 5:1, 102-114

Statistical Methods and Models

Bayesian Estimation and Inference for Generalized Partial Linear Models Using Shape-Restricted Splines

Authors: Mary C. Meyer, Jennifer A. Hoeting, and Amber Hackstadt (2009).

Submitted

Bayesian analysis of abundance for binomial sighting data with unknown number of marked individuals

Authors: B. T. McClintock and J. A. Hoeting

Ecological and Environmental Statistics, DOI 10.1007/s10651-009-0109-0 (online until print version is published).

Biological monitoring: A Bayesian Model for Multivariate Compositional Data
Authors: D. S. Johnson, J. A. Hoeting, and N. L. Poff
Bayesian Statistics and its Applications, Eds. S. K. Upadhyay, U. Singh and D. K. Dey.
Anamaya publishers: New Delhi, p 270-289. Note: preprint has some minor typos.

Random Effects Graphical Models for Multiple Site Sampling
Authors: Devin Johnson and Jennifer A. Hoeting
CSU Technical Report 2003/15

Autoregressive Models for Capture-Recaputure Data: A Bayesian Approach
Authors: Devin S. Johnson and Jennifer A. Hoeting
Biometrics, 2003, vol 59, 340-349

Transform Estimation of Parameters for Stage-Frequency Data
Authors: J. A. Hoeting, R. L. Tweedie, C.S. Olver
Journal of American Statistical Association 98:463, 503-514.

Empirical Transform Estimation of Parameters in the Monomolecular Growth Model
Authors: Devin S. Johnson, Jennifer A. Hoeting, Richard L. Tweedie
Technical Report 2001-3, Department of Statistics, Colorado State University.

Applications

Linking Chronic Wasting Disease to Mule Deer Movement Scales: A Hierarchical Bayesian Approach
Authors: M. L. Farnsworth, J. A. Hoeting. N. T. Hobbs, M. W. Miller
Ecological Applications, 2006

Interdisciplinary Irrigated Precision Farming Research
Authors: Heermann, D.F., J. A. Hoeting, S. E. Thompson, et al.
Precision Agriculture, 2002

Predicting Colorado River Sandbar Size Using Glen Canyon Dam Release Characteristics
Final Report for the National Park Service
Authors: Jennifer A. Hoeting, Kristina Varga, Brian Cluer
Submitted to National Park Service
Date: Jan 1997

Sandbars in the Colorado River: an Environmental ConsultingProject
Author: Jennifer A. Hoeting
Statistical Science, 13, 9-13
Date: 1998

Are the fish safe to eat? Assessing mercury levels in Maine lakes (a case study)
Authors: Jennifer Hoeting and Anthony R. Olsen
Statistical Case Studies: A Collaboration Between Academe and Industry, 1998,
R. Peck, L. Haugh, A. Goodman, editors, pages 1-6. ASA-SIAM.