## A statement of principleI do not accept funding from organizations active in national security, military, surveillance and similar areas, nor will I collaborate with individuals associated with those. This exclusion reflects a deeply-held belief that the militarization of science and research is detrimental to human progress towards peace and equitable distribution of resources. As a researcher, I consider it my responsibility that my work not cause harm to other people, either directly or indirectly, and as an educator, I strive to demonstrate this commitment in my professional activities. ## Selected publications: submitted/acceptedBreidt, F.J. and J.D. Opsomer (2016). “Model-assisted survey estimation with modern prediction techniques.” Invited submission to Yu, H., Y. Wang, P. Wang, J.D. Opsomer and N. Ponce (2016). “A design-based approach to small area estimation using semiparametric generalized linear mixed models.” Submitted to Baik, E., E. Larson and J.D. Opsomer (2015). “Methane Leakage Uncertainty.” Submitted to Hernandez-Stumpfhauser, D., F.J. Breidt and J.D. Opsomer (2015). “Hierarchical Bayesian Small Area Estimation for Circular Data.” Accepted in Wu, J., M.C. Meyer and J.D. Opsomer (2015). Survey estimators that respect natural orderings. Accepted in F.J. Breidt, J.D. Opsomer and I. Sanchez Borrego (2015). Nonparametric Variance Estimation under Fine Stratification: An Alternative to Collapsed Strata. To appear in L. You and J.D. Opsomer (2014). Cross-Validation in Penalized Spline Model-Assisted Estimation. Under revision for ## Selected publications: in printD. Hernandez-Stumpfhauser, F.J. Breidt and J.D. Opsomer (2016). "Variational Approximations for Selecting Hierarchical Models of Circular Data in a Small Area Estimation Application." Ranalli, M.G., F.J. Breidt and J.D. Opsomer (2016). "Nonparametric regression methods for small area estimation." J.D. Opsomer, F.J. Breidt, M. White and Y. Li (2016). "Successive Difference Replication Variance Estimation in Two-Phase Sampling." Wang, Y., N. Ponce, P. Wang, J.D. Opsomer and H. Yu (2015). “Generating Health Estimates by Zip Code: A Semi-parametric
Small Area Estimation Approach Using the California Health Interview
Survey.” Zimmerle, D.J., L.L. Williams, T.L. Vaughn, C. Quinn, R.
Subramanian, G.P. Duggan, B. Willson, J.D. Opsomer, A. Marchese, D.M.
Martinez, A.L. Robinson (2015). “Methane emissions from the natural gas transmission and storage system in the United States.” He, Z. and J.D. Opsomer (2015). "Local Polynomial Regression with an Ordinal Covariate." Wu, J., M.C. Meyer and J.D. Opsomer (2015). "Penalized isotonic regression." J.C. Wang, J.D. Opsomer and H. Wang (2014). "Bagging non-differentiable estimators in complex surveys." I. Sanchez-Borrego, J.D. Opsomer, M. Rueda and A. Arcos (2014).
"Nonparametric estimation with mixed data types in survey sampling." L. Diao, D.D. Smith, G. Datta, T. Maiti and J.D. Opsomer (2014).
“Accurate Confidence Interval Estimation of Small Area Parameters under
the Fay-Herriot Model.” Wang, H., M.C. Meyer and J.D. Opsomer (2013). "Constrained Spline Regression in the Presence of AR(p) Errors." J.R. Tipton, J.D. Opsomer, G.G. Moisen, G.G. (2013). “Properties of
the Endogenous Post-Stratified Estimator Using a Random Forest Model.” J.D. Opsomer (2013). “Nonparametric regression model.” Encyclopedia of Environmetrics Second Edition, A.-H. El-Shaarawi and W. Piegorsch (eds). John Wiley & Sons Ltd, Chichester, UK, 1798-1811 (DOI: 10.1002/9780470057339.van019.pub2). M. Dahlke, F.J. Breidt, J.D. Opsomer and I. Van Keilegom (2013). “Nonparametric endogenous post-stratification in surveys.” J.W. Karl, M.C. Duniway, S.M. Nusser, J.D. Opsomer and R.S. Unnasch
(2012). “Using VHR Imagery for Rangeland Monitoring and Assessment:
Some Statistical Considerations.” J.D. Opsomer, M. Francisco-Fernandez and X. Li (2012). “Variance
estimation for systematic sampling designs using nonparametric
regression.” J.D. Opsomer (2011). “Innovations in Survey Sampling Design:
Discussion of Three Contributions Presented at the U.S. Census Bureau.” G. Kauermann and J.D. Opsomer (2011). Data-driven Selection of the Spline Dimension in Penalized Spline Regression. Biometrika, 98, 91-106.
J.D. Opsomer and F.J. Breidt (2011). Nonparametric regression using kernel and spline methods. International Encyclopedia of Statistical Science, Miodrag Lovric (editor), Springer, Part 14, 974-977. J.D. Opsomer and M. Francisco-Fernandez (2010). Finding Local
Departures from a Parametric Model Using Nonparametric Regression. G. Kauermann, G. Claeskens and J.D. Opsomer (2009). Bootstrapping for Penalized Spline Regression. da Silva, D.N. and J.D. Opsomer (2009). Nonparametric propensity
weighting for survey nonresponse through local polynomial regression. J.D. Opsomer (2009). Alternative approaches to inference from survey data, in Breidt, F.J. and J.D. Opsomer (2009). Nonparametric and semiparametric estimation in complex surveys, in G. Claeskens, T. Krivobokova and J.D. Opsomer (2009). Asymptotic properties of penalized spline estimators. A.A. Johnson, F.J. Breidt and J.D. Opsomer (2008). Estimating
distribution functions from survey data using nonparametric regression.
F.J. Breidt and J.D. Opsomer (2008). Endogenous post-stratification in surveys: classifying with a sample-fitted model. J.D. Opsomer, G. Claeskens, M.G. Ranalli, G. Kauermann and F.J.
Breidt (2008). Nonparametric small area estimation using penalized
spline regression. Breidt, F.J. and J.D. Opsomer (2007). Discussion of `Struggles with survey weighting and regression modeling’ by A. Gelman. F.J. Breidt, J.D. Opsomer, A.A. Johnson and M.G. Ranalli (2007).
Semiparametric model-assisted estimation for natural resource surveys. J.D. Opsomer, F.J. Breidt, G.G. Moisen and G. Kauermann (2007).
Model-assisted estimation of forest resources with generalized additive
models (with discussion). D. N da Silva and J.D. Opsomer (2006). A kernel smoothing method to adjust for unit nonresponse in sample surveys. M. Francisco-Fernandez, M. Jurado-Exposito, J.D. Opsomer and F.
Lopez-Granados (2006). A nonparametric analysis of the distribution of R.M. Cruse, D. Flanagan, J. Frankenberger, B.K. Gelder, D.
Herzmann, D. James, W. Krajewski, M. Kraszewski, J.M. Laflen, J.D.
Opsomer, and D. Todey (2006). Daily estimates of rainfall, water runoff,
and soil erosion in Iowa. F.J. Breidt, G. Claeskens and J.D. Opsomer (2005). Model-assisted estimation for complex surveys using penalized splines. M. Francisco-Fernandez and J.D. Opsomer (2005), Smoothing Parameter
Selection Methods for Nonparametric Regression with Spatially
Correlated Errors. J.D. Opsomer and C.P. Miller (2005). Selecting the Amount of
Smoothing in Nonparametric Regression Estimation for Complex Surveys. P. Hall and J.D. Opsomer (2005). Theory for penalised spline regression. D.N. da Silva and J.D. Opsomer (2004). Properties of the Weighting Cell Estimator under a Nonparametric Response Mechanism. M. Francisco-Fernandez, J.D. Opsomer and J. Vilar-Fernandez (2004),
A plug-in bandwidth selector for local polynomial regression estimator
with correlated errors. G. Kauermann and J.D. Opsomer (2004). Generalized cross-validation
for bandwidth selection of backfitting estimators in generalized
additive models. G. Kauermann and J.D. Opsomer (2003). Local
likelihood estimation in generalized additive models. J.D. Opsomer, C. Botts and J.Y. Kim (2003). Small
area estimation in a watershed erosion assessment survey. J.D. Opsomer, H.H. Jensen and S. Pan (2003). An Evaluation of the USDA Food
Security Measure with Generalized Linear Mixed Models. J.D. Opsomer (2002). Nonparametric regression model. J.D. Opsomer, Y. Wang and Y. Yang (2001). Nonparametric regression with correlated
errors. F.J. Breidt and J.D. Opsomer (2000). Local polynomial regression estimators
in survey sampling. J.D. Opsomer (2000). Asymptotic properties of backfitting estimators. J.D. Opsomer and D. Ruppert (1999). A root-n consistent estimators for semi-parametric additive models, J.D. Opsomer, D. Ruppert, M.P. Wand, U. Holst and O. Hossjer (1999). Kriging with nonparametric variance function estimation. J.D. Opsomer and S.M. Nusser (1999). Sample designs for watershed assessment. J.D. Opsomer and D. Ruppert (1998). A fully automated bandwidth selection method for fitting additive models. J.D. Opsomer (1997). Nonparametric regression in the presence of correlated errors, in J.D. Opsomer and D. Ruppert (1997). Fitting a bivariate additive model by local polynomial regression. J.D. Opsomer, J. Agras, A. Carpi and G. Rodrigues (1995). An
application of locally weighted regression to airborne mercury
deposition around an incinerator site. J.D. Opsomer and J. M. Conrad (1994). An open-access analysis of the Northern Anchovy fishery. ## Technical Reports
J.D. Opsomer, M. Francisco-Fernandez and X. Li (2012). Supporting Materials for "Model-based nonparametric variance estimation for systematic sampling in a forestry survey." G. Kauermann and J.D. Opsomer (2010). Data-driven Selection of the Spline Dimension in Penalized Spline Regression: Supplementary Materials. J.Y Kim, F.J. Breidt and J.D. Opsomer (2009). Nonparametric Regression Estimation of Finite Population Totals under Two-Stage Sampling. Technical Report #2009/4, Department of Statistics, Colorado State University. D.N. da Silva and J.D. Opsomer (2008). Theoretical properties of propensity weighting for survey nonresponse through local polynomial regression. Technical Report #2008/6, Department of Statistics, Colorado State University. C.P. Miller and J.D. Opsomer (2004). Theorems on Bandwidth Selection for Local Polynomial Regression with Survey Data. Preprint Series #04-18, Department of Statistics, Iowa State University. J.D. Opsomer and G. Kauermann (2000). Weighted local polynomial regression, weighted additive models and local scoring. Preprint Series #00-7, Department of Statistics, Iowa State University. Last updated: June 10, 2016. |