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Nonparametric regression: my current interests in this area are in the development of penalized spline regression methodology, and on the application of nonparametric regression techniques in survey statistics (see below).
Environmental statistics: I seek to develop advanced statistical tools to increase our understanding of environmental processes as well as the human impact on the environment. My primary areas of application are environmental economics, environmental toxicology and natural resource surveys. I have collaborated with faculty in the Department of Agronomy at Iowa State University on building a daily erosion prediction model for Iowa, and I was involved in a watershed-level agro-ecological experiment to assess the feasibility and impacts of combining native prairie and intensive agriculture in Iowa.
Survey statistics: I have been involved in the design and estimation for the National Resources Inventory (NRI) survey, as well as several other surveys conducted by the Center for Survey Statistics and Methodology at Iowa State University. On the methodological side, I have been collaborating with Jay Breidt from Colorado State University on the development of nonparametric model-assisted estimation techniques. More recently, I have been applying nonparametric methods in survey estimation problems, including small area estimation, imputation, and variance estimation.
F.J. Breidt and J.D. Opsomer (2008). Endogenous post-stratification in surveys: classifying with a sample-fitted model. Annals of Statistics, 36, 403-427.
J.D. Opsomer, G. Claeskens, M.G. Ranalli, G. Kauermann and F.J. Breidt (2008). Nonparametric small area estimation using penalized spline regression. Journal of the Royal Statistical Society, Series B, 70, 265-286.
Breidt, F.J. and J.D. Opsomer (2007). Discussion of `Struggles with survey weighting and regression modeling’ by A. Gelman. Statistical Science, 22, 168-170.
F.J. Breidt, J.D. Opsomer, A.A. Johnson and M.G. Ranalli (2007). Semiparametric model-assisted estimation for natural resource surveys. Survey Methodology, 33, 35-44.
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). Journal of the American Statistical Association, 102, 400-416.
D. N da Silva and J.D. Opsomer (2006). A kernel smoothing method to adjust for unit nonresponse in sample surveys. Canadian Journal of Statistics, 34, 563-579.
M. Francisco-Fernandez, M. Jurado-Exposito, J.D. Opsomer and F. Lopez-Granados (2006). A nonparametric analysis of the distribution of Convolvulus arvensis in wheat-sunflower rotations. Environmetrics, 17, 849-860.
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. Journal of Soil and Water Conservation, 61, 191-199.
F.J. Breidt, G. Claeskens and J.D. Opsomer (2005). Model-assisted estimation for complex surveys using penalized splines. Biometrika, 92, 831-846.
M. Francisco-Fernandez and J.D. Opsomer (2005), Smoothing Parameter Selection Methods for Nonparametric Regression with Spatially Correlated Errors. Canadian Journal of Statistics, 33, 279-295.
J.D. Opsomer and C.P. Miller (2005). Selecting the Amount of Smoothing in Nonparametric Regression Estimation for Complex Surveys. Journal of Nonparametric Statistics, 17, 593-611.
P. Hall and J.D. Opsomer (2005). Theory for penalised spline regression. Biometrika, 92, 105-118.
D.N. da Silva and J.D. Opsomer (2004). Properties of the Weighting Cell Estimator under a Nonparametric Response Mechanism. Survey Methodology, 30, 45-55.
M. Francisco-Fernandez, J.D. Opsomer and J. Vilar-Fernandez (2004), A plug-in bandwidth selector for local polynomial regression estimator with correlated errors. Journal of Nonparametric Statistics, 16, 127-151.
G. Kauermann and J.D. Opsomer (2004). Generalized cross-validation for bandwidth selection of backfitting estimators in generalized additive models. Journal of Computational and Graphical Statistics, 13, 66-89.
G. Kauermann and J.D. Opsomer (2003). Local likelihood estimation in generalized additive models. Scandinavian Journal of Statistics, 30, 317-337.
J.D. Opsomer, C. Botts and J.Y. Kim (2003). Small area estimation in a watershed erosion assessment survey. Journal of Agricultural, Biological and Environmental Statistics, 8, 139-152.
J.D. Opsomer, H.H. Jensen and S. Pan (2003). An Evaluation of the USDA Food Security Measure with Generalized Linear Mixed Models. Journal of Nutrition, 133, 421-427.
J.D. Opsomer (2002). Nonparametric regression model. Encyclopedia of Environmetrics, A.H. El-Shaarawi and W.W. Piegorsch (editors), Wiley & Sons, Chichester U.K., Volume 3, 1411-1425.
J.D. Opsomer, Y. Wang and Y. Yang (2001). Nonparametric regression with correlated errors. Statistical Science, 16, 134-153.
F.J. Breidt and J.D. Opsomer (2000). Local polynomial regression estimators in survey sampling. Annals of Statistics, 28, 1026-1053.
J.D. Opsomer (2000). Asymptotic properties of backfitting estimators. Journal of Multivariate Analysis, 73,166-179.
J.D. Opsomer and D. Ruppert (1999). A root-n consistent estimators for semi-parametric additive models, Journal of Computational and Graphical Statistics, 8:715-732.
J.D. Opsomer, D. Ruppert, M.P. Wand, U. Holst and O. Hossjer (1999). Kriging with nonparametric variance function estimation. Biometrics, 55, 704-710.
J.D. Opsomer and S.M. Nusser (1999). Sample designs for watershed assessment. Journal of Agricultural, Biological and Environmental Statistics, 4, 429-442.
J.D. Opsomer and D. Ruppert (1998). A fully automated bandwidth selection method for fitting additive models. Journal of the American Statistical Association, 93, 605-619. To download the additive model fitting program described in this paper, see below.
J.D. Opsomer (1997). Nonparametric regression in the presence of correlated errors, in Modelling Longitudinal and Spatially Correlated Data: Methods, Applications and Future Directions, T.G. Gregoire, D.R. Brillinger, P.J. Diggle, E. Russek-Cohen, W.G. Warren and R.D. Wolfinger (editors), Springer, New York, 339-348.
J.D. Opsomer and D. Ruppert (1997). Fitting a bivariate additive model by local polynomial regression. Annals of Statistics, 25, 186-211.
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. Environmetrics, 6, 205-221.
J.-D. Opsomer and J. M. Conrad (1994). An open-access analysis of the Northern Anchovy fishery. Journal of Environmental Economics and Management, 27, 21-37.
Diao, L., T. Maiti and J.D. Opsomer (2008). Accurate Confidence Interval Estimation of Small Area Parameters under the Fay-Herriot Model. Submitted to Scandinavian Journal of Statistics.
Claeskens, G., T. Krivobokova and J.D. Opsomer (2008). Asymptotic properties of penalized spline estimators. Submitted to Biometrika.
Wang, J. and J.D. Opsomer (2008). Estimating the distance distribution of subpopulations for a large-scale complex survey. Submitted to Annals of Statistics.
J.D. Opsomer and M. Francisco-Fernandez (2008). Finding Local Departures from a Parametric Model Using Nonparametric Regression. To appear in Statistical Papers.
Breidt, F.J. and J.D. Opsomer (2007). Nonparametric and semiparametric estimation in complex surveys. To appear in Handbook of Statistics, Vol. 29: Sample Surveys: Theory, Methods and Inference, C.R. Rao and D. Pfeffermann (editors), North Holland, Amsterdam.
G. Kauermann, G. Claeskens and J.D. Opsomer (2006). Bootstrapping for Penalized Spline Regression. Preprint Series #06-01, Department of Statistics, Iowa State University. Resubmitted to Journal of Computational and Graphical Statistics.
A.A. Johnson, F.J. Breidt and J.D. Opsomer (2004). Estimating distribution functions from survey data using nonparametric regression. Preprint Series #04-07, Department of Statistics, Iowa State University. To appear in Journal of Statistical Theory and Practice.
J.Y Kim, F.J. Breidt and J.D. Opsomer (2003). Nonparametric Regression Estimation of Finite Population Totals under Two-Stage Sampling. Preprint Series #03-06, Department of Statistics, Iowa State University. Under revision for Survey Methodology.
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.
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National Research Council (2007). “Understanding American Agriculture: Challenges for the Agricultural Resource Management Survey.” National Academies Press, Washington, D.C. I was a member of the NRC Panel to Review USDA's Agricultural Resource Management Survey. | |||||||||
J.D. Opsomer, H.H. Jensen, S.M. Nusser, D. Drignei, Y. Amemiya (2002). Statistical Considerations for the USDA Food Insecurity Index. Publication #02-WP 307, Center for Agricultural and Rural Development, Iowa State University.
J.D. Opsomer, Z. Wu, T. Isenhart, V. Sitzmann, T.J. Jacobsen, J.Y. Kim, C. Botts (2001). Environmental Assessment for the Rathbun Lake Watershed: Sampling Design, Methods and Results. Preprint Series #01-13, Department of Statistics, Iowa State University.
B.F. McQuaid and L. Norfleet (1999). Assessment of two Carolina watersheds using land and stream habitat quality indices. Journal of Soil and Water Conservation, 657-665. See Opsomer and Nusser (1999) reference above for the methodology.
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Last updated: May 27, 2008.