### Journal Publications

1. Reinsel, G., Tiao, G. C., Wang, M. N., Lewis, R. and Nychka, D. (1981). “Statistical Analysis of Stratospheric Ozone Data for the Detection of Trends.” Atmospheric Environment, 15, 1569-1577.

2. Koen, J., Pugh, T., Nychka, D. and Goldfarb, S. (1983). “Presence of β-fetoprotein Positive Cells in Hepatocellular Foci Induced by Single Injection of Dimethylnitrosamine in Infant Mice.” Cancer Research, 43, 702-708.

3. Pugh, T. D., King, J. H., Koen, H., Nychka, D., Chover, J., Wahba, G., He, Y. and Goldfarb, S. (1983). “A Reliable Mathematical Stereologic Method for Estimating the Number of Hepatocellular Foci from their Transections.” Cancer Research, 43, 1261-1268.

4. Nychka, D., Pugh, T., King, J., Koen, H., Wahba, G., Chover, J. and Goldfarb, S. (1984). “Optimal Use of Sampled Tissue Sections for Estimating the Number of Hepatocellular Foci.” Cancer Research, 44, 178-183.

5. Nychka, D., Wahba, G., Pugh, T. D. and Goldfarb, S. (1984). “Cross-Validated Spline Methods for the Estimation of Three-Dimensional Tumor Size Distributions from Observations on Two-Dimensional Cross Sections.” Journal of the American Statistical Association, 79, 832-846.

6. Gallant, A. R. and Nychka, D. (1987). “Semi-nonparametric Maximum Likelihood Estimation.” Econometrica, 15, 363-390.

7. Nychka, D. (1988). “Bayesian ‘Confidence’ Intervals for Smoothing Splines.” Journal of the American Statistical Association, 83, 1134-1143.

8. Nychka, D. and Cox, D. D. (1989). “Convergence Rates for Regularized Solutions of Integral Equations from Discrete Noisy Data.” Annals of Statistics, 17, 556-572.

9. Nychka, D. (1990). “The Average Posterior Variance of a Smoothing Spline and a Consistent Estimate of the Averaged Squared Error.” Annals of Statistics, 18, 415- 428.

10. Nychka, D. (1990). “Some Properties of Adding a Smoothing Step to the EM Algorithm.” Statistics and Probability Letters, 9, 187-193.

11. Silverman, B. W., Jones, M. C., Wilson, J. D. and Nychka, D. W. (1990). “A Smoothed EM Approach to a Class of Problems in Image Analysis and Integral Equations,” with discussion in Journal of the Royal Statistical Society Series B, 52, 271-324.

12. Nychka, D., Ellner, S., McCaffrey, D. and Gallant, A. R. (1990). “Statistics for Chaos.” Statistical Computing and Graphics Newsletter, American Statistical Association, Volume 1.

13. Ellner, S., Gallant, A. R., McCaffrey, D. and Nychka, D. (1991). “Converge Rates and Data Requirements for Jacobian-based Estimates of Lyapunov Exponents from Data.” Physics Letters, 153, 357-363.

14. Nychka, D. (1991). “Choosing a Range for the Amount of Smoothing in Nonparametric Regression.” Journal of the American Statistical Association, 86, 653-664.

15. Bloomfield, P. and Nychka, D. (1992). “Climate Spectra and Detecting Climate Change.” Climatic Change, 21, 275-287.

16. McCaffrey, D., Nychka, D., Ellner, S. and Gallant, A. R. (1992). “Estimating Lyapunov Exponents with Nonparametric Regression.” Journal of the American Statistical Association, 87, 682-695.

17. Nychka, D., Ellner, S., McCaffrey, D. and Gallant, A. R. (1992). “Finding Chaos in Noisy Systems.” Journal of the Royal Statistical Society Series B, 54, 399-426.

18. Meier, K. and Nychka, D. (1993). “Nonparametric Estimation of Rate Equations for Nutrient Uptake.” Journal of The American Statistical Association, 88, 602-614.

19. Schluter, D. and Nychka, D. (1993). “Exploring Fitness Surfaces.” American Naturalist, 143, 597-616.

20. Haaland, P., McMillan, N., Nychka, D. and Welch, W. (1994). “Analysis of Spacefilling Designs.” Computing Science and Statistics: Computationally Intensive Statistical Methods, 26, 111-120.

21. O’Connell, M. and Nychka, D. (1995). “A Generalized Linear Classification Model with a Smooth Link Function and Predictors Obtained from Quantile Spline Fits to High-Dimensional Data.” Journal of Statistical Planning and Inference, 45, 153-164.

22. Nychka, D. and Ruppert, D. (1995). “A Nonparametric Transformation Applied to Both Sides of a Regression Model.” Journal of the Royal Statistical Society, Series B, 57, 519-532.

23. Graham, M., Paulos, J. and Nychka, D. (1995). “Template-based MOSFET Device Model”. IEEE Transactions on CAD/ICAS, 14, 924-933.

24. Nychka, D. (1995). “Smoothing Splines as Locally Weighted Averages.” Annals of Statistics, 23, 1175-1197.

25. Nychka, D. W., Ellner, S. and Bailey, B. A. (1995). “A Personal Overview of Nonlinear Time-series Analysis from a Chaos Perspective - Discussion and Comments.” Scandinavian Journal of Statistics, 22, 433-435.

26. Nychka, D., Gray, G., Haaland, P., Martin, D. and O’Connell, M. (1995). “A Nonparametric Regression Approach to Syringe Grading for Quality Improvement.” Journal of the American Statistical Association, 90, 1171-1178.

27. Nychka, D. and O’Connell, M. (1996). “Neural Networks in Applied Statistics - Discussion.” Technometrics, 38, 218-220.

28. Nychka, D., Yang, Q. and Royle, J. A. (1997). “Constructing Spatial Designs Using Regression Subset Selection.” Statistics for the Environment-3: Pollution Assessment and Control, eds. Barnett, V. and Turkman, K. F., Wiley, New York.

29. Royle, J. A. and Nychka, D. (1997). “An Algorithm for the Construction of Spatial Designs with an Implementation in SPLUS.” Computers and Geosciences, 24, 479-488.

30. Ellner, S., Bailey, B., Bobashev, G., Gallant, A. R., Grenfell, B. and Nychka, D. (1998). “Noise and Nonlinearity in Measles Epidemics: Combining Mechanistic and Statistical Approaches to Population Modeling.” American Naturalist, 151, 425-440.

31. Nychka, D. and Saltzman, N. (1998).“Design of Air Quality Monitoring Networks.” Case Studies in Environmental Statistics, ed. Nychka, D., Cox, L., Piegorsch, W., Lecture Notes in Statistics, Springer-Verlag.

32. Davis, J. M., Eder, B., Nychka, D. and Yang, Q. (1998). “Modeling the Effects of Meteorology on Ozone in Houston Using Cluster Analysis and Generalized Additive Models.” Atmospheric Environment, 32, 2505-2520.

33. Holland, D., Saltzman, N., Cox, L. and Nychka, D. (1998). “Spatial Prediction of Sulfur Dioxide in the Eastern United States.” Proceedings of geoENV98, Valencia, Spain, November 1998, Kluwer.

34. Tsai, K., Brownie, C., Nychka, D. W. and Pollock, K. H. (1999). “Smoothing Hazard Functions for Telemetry Survival Data in Wildlife Studies.” Bird Study 46, 47-54, Suppl. S 1999.

35. Errico, R. M., Fillion, L., Nychka, D. and Lu, Z.-Q. (2000). “Some Statistical Considerations Associated with the Data Assimilation of Precipitation Observations.” Quarterly Journal of the Royal Meteorological Society, 126, 339-359, Part A.

36. Huang, J.-C. and Nychka, D. (2000). “A Nonparametric Multiple Choice Model within the Random Utility Framework.” Journal of Econometrics, 2, 207-225.

37. Davis, J. M., Nychka, D. and Bailey, B. (2000). “A Comparison of the Regional Oxidant Model with Observed Data.” Atmospheric Environment, 34, 2413-2423.

38. Santer, B. D., Wigley, T. M. L., Boyle, J. S., Gaffen, D. J., Hnilo, J. J., Nychka, D., Parker, D. E. and Taylor, K. E. (2000). “Statistical Significance of Trends and Trend Differences in Layer-average Atmospheric Temperature Time Series.” Journal of Geophysical Research–Atmosphere, 105, 7337-7356.

39. Nychka, D. (2000). “Challenges in Understanding the Atmosphere.” Journal of the American Statistical Association, 95, 972-975. See also Statistics in the 21st Century, ed., Raftery, A., Tanner, M. and Wells, M., Chapman and Hall/CRC, New York, 199-206.

40. Cummins, D. J., Filloon, T. G. and Nychka, D. (2001). “Confidence Intervals for Nonparametric Curve Estimates: Toward more Uniform Pointwise Coverage.” Journal of the American Statistical Association, 96, 233-246.

41. Small, E. E., Sloan, L. C. and Nychka, D. (2001). “Changes in Surface Air Temperature Caused by Desiccation of the Aral Sea.” Journal of Climate, 14, 284-299.

42. Tebaldi, C., Branstator, G. and Nychka, D. (2001). “Looking for Nonlinearities in the Large Dynamics of the Atmosphere.” Proceedings of 1st SIAM Conference on Scientific Data Mining.

43. Wikle, C., Milliff, R., Nychka, D. and Berliner, L. M. (2001). “Spatiotemporal Hierarchical Bayesian Modeling: Tropical Ocean Surface Winds.” Journal of American Statistical Association, 96, 382-397.

44. Matsuo, T., Nychka, D., Richmond, A. (2002). “Modes of high-latitude electric field variability derived from DE-2 measurements: Empirical Orthogonal Function (EOF) Analysis.” Geophysical Research Letters. 29 (7), doi:10.1029/2001GL014077.

45. Nychka, D., Wikle, C. and Royle, J. A. (2002). “ Multiresolution models for nonstationary spatial covariance functions.” Statistical Modelling. 2, 315-332.

46. Tebaldi, C., Nychka, D., Brown, B.G. and Sharman, B. (2002). “Flexible discriminant techniques for forecasting clear-air turbulence.” Environmetrics, 13, 859-878.

47. Bengtsson, T., Snyder, C. and Nychka, D. (2003) A nonlinear filter that extends to high dimensional systems Journal of Geophysical Research -Atmosphere, 108, 1-10.

48. Johns, C. Nychka, D. Kittel, T., Daly, C. (2003). “Infilling Sparse Records of Precipitation Fields.” Journal of the American Statistical Association, 98, 796–806.

49. Holland, D. Cox, W.M., Scheffe, R., Cimorelli, A., Nychka, D. and Hopke, P. (2003). “Spatial Prediction of Air Quality Data.” Environmental Manager, August.

50. Milliff, R.F., Niiler,P.P ,Morzel, J., Sybrandy,A.E. Nychka, D. and Large, W.G. (2003).

“Mesoscale Correlation Length Scales from NSCAT and MiniMET Surface Wind Retrievals.” Journal of Atmospheric and Oceanic Technology, 20(4), 513-533.

51. Oh, H.-S., Ammann, C.M., Naveau, P., Nychka,D. Otto-Bliesner, B. L. (2003) “Multiresolution time series analysis applied to solar irradiance and climate reconstructions.” Journal of Atmospheric and Solar-Terrestrial Physics, 2, 191-201.

52. Hoar, T., Milliff, R., Nychka, D., Wikle, C., Berliner, L.M. (2003). “Winds from a Bayesian Hierarchical Model: Computation for Atmosphere-Ocean Research.” Journal of Computational and Graphical Statistics, 12, 781-807.

53. Meehl, G.A., Tebaldi,C. and Nychka, D. (2004). “Changes in frost days in simulations of 21st century climate.” Climate Dynamics DOI: 10.1007/s00382-004-0442-9.

54. Oh, H-S, Nychka, D. Brown, T. and Charbouneau, P. (2004). “Periodic Analysis of Variable Stars by Robust Smoothing.” Journal of the Royal Statistical Society Series C. 53, 15–30.

55. Gilleland, E. and Nychka, D. (2005) “Statistical Models for Monitoring and Regulating Ground-level Ozone” Environmetrics. 16, 535–546.

56. Tebaldi, C. R. L. Smith, D. Nychka, and L. Mearns (2005) “Quantifying Uncertainty in Projections of Regional Climate Change: A Bayesian Approach to the Analysis of Multimodel Ensembles” Journal of Climate,18, 1524–1540.

57. Feddema, J., K. Oleson, G. Bonan, L. Mearns, W. Washington, G. Meehl, and D. Nychka (2005). “A Comparison of GCM response to historical anthropongenic land cover change and model sensitivity to uncertainty in present-day land cover representations.” Climate Dynamics, 25, 581-609, DOI 10.1007/s00382-005-0038-z.

58. Fuentes, M., T.G.F. Kittel, and D. Nychka (2006) “Sensitivity of ecological models to spatial-temporal estimation of their climate drivers: Statistical ensembles for forcing.” Ecological Applications, 16, pp. 99-116

59. Bengtsson, T., R.F. Milliff, R Jones, D. Nychka, P. Niiler (2005). “A state space model for ocean drifter motions dominated by inertial oscillations.” Journal of Geophysical Research- Oceans. 110, C10015, doi:10.1029/2004JC002850.

60. Furrer, R. M. Genton, and D. Nychka (2006) “Covariance tapering for interpolation of large spatial datasets.” Journal of Computational and Graphical Statistics 15(3), 502-523.

61. Sain, S., J. Shirkant, L. Mearns and D. Nychka (2006). “A multivariate spatial model for soil water profiles. ” Journal of Agricultural Biological and Environmental Statistics 11(4) 462-480.

62. Cooley, D. D. Nychka, and P. Naveau. (2007) “Bayesian Spatial Modeling of Extreme Precipitation Return Levels.” Journal of the American Statistical Association, 102, 824-840.

63. Furrer, R., R. Knutti, S. R. Sain, D. W. Nychka, and G. A. Meehl (2007), “Spatial patterns of probabilistic temperature change projections from a multivariate Bayesian analysis”, Geophysical Research Letters, 34, L06711, doi:10.1029/2006GL027754.

64. Oh, H-S, D. Nychka and T. Lee. (2007). “The role of pseudodata for robust smoothing with application to wavelet regression.” Biometrika doi: 10.1093/biomet/asm064.

65. Smith, R.L., C. Tebaldi, D. Nychka and L.O.Mearns (2008). “Bayesian Modeling of Uncertainty in Ensembles of Climate Models.” Journal of the American Statistical Association In press.

66. Furrer, E. M. and D. W. Nychka. (2007). “A framework to understand the asymptotic properties of Kriging and splines.” Journal of the Korean Statistical Society 36, 57-76.

67. Jun, M., R. Knutti and D. Nychka.(2007). “Spatial Analysis to Quantify Numerical Model Bias and Dependence: How Many Climate Models Are There?” Journal of the American Statistical Association,103, 934-947.

68. Furrer, R, Sain, S. R., Nychka, D., and Meehl, G. A. (2007). “Multivariate Bayesian Analysis of Atmosphere-Ocean General Circulation Models.” Environmental and Ecological Statistics, 14(3), 249-266, doi:10.1007/s10651-007-0018-z.

69. Li, B., C. Ammann, D.Nychka. (2007).“The “Hockey Stick” and the 1990s: A Statistical Perspective on Reconstructing Hemispheric Temperatures.” Tellus, 59, 591-598.

70. M. Jun, R. Knutti and D. Nychka. (2008) “Spatial Analysis to Quantify Numerical Model Bias and Dependence: How Many Climate Models Are There? ” Journal of the American Statistical Association 103(483): 934-947

71. Whitcher, B., T. C. M. Lee, J. B. Weiss, T. J. Hoar and D. W. Nychka (2008). “A Multiresolution Census Algorithm for Calculating Vortex Statistics in Turbulent Flows”, Journal of the Royal Statistical Society Series C (Applied Statistics), 57: 293312.

72. Kaufman, C., Schervish, M., and Nychka, D. (2008) “Covariance Tapering for Likelihood-Based Estimation in Large Spatial Datasets” Journal of the American Statistical Association 103(484): 1545-1555.

73. A. Malmberg, A. Arellano, D. P. Edwards, N. Flyer, D. Nychka, C. Wikle. (2008) “Interpolating Fields of Carbon Monoxide Data using a Hybrid Statistical-Physical Model” Annals of Applied Statistics., 2(4), 1231-1248.

74. Jun, M., R. Knutti, and D W. Nychka (2008). Local eigenvalue analysis of CMIP3 climate model errors. Tellus A, 60, 992-1000.

75. Huang, J-C, K.V. Smith, D Nychka (2008). Semi-parametric Discrete Choice Measures of Willingness to Pay. Economics Letters, DOI:10.1016/j.econlet.2008.06.010.

76. Khare S. P., Anderson J. L., Hoar T. J., Nychka D., (2008). An Investigation into the Application of an Ensemble Kalman Smoother to High-Dimensional Geophysical Systems. Tellus A. 60: 97-112.

77. Romero-Lankao, P., J. L. Tribbia and D. Nychka (2008) Development and greenhouse gas emissions deviate from the modernization theory and convergence hypothesis. Climate Research 38, 17-29.

78. Santer, B., P. W. Thorne, L. Haimberger, K. E. Taylor, T. M. L. Wigley, J. R. Lanzante, S. Solomon, M. Free, P. J. Gleckler, P. D. Jones, T. R. Karl, S. A. Klein, C. Mears, D. Nychka, G. A. Schmidt, S. C. Sherwood,l and F. J. Wentz (2008) Consistency of modelled and observed temperature trends in the tropical troposphere. International Journal of Climatology 28: 17031722

79. Storlie, C., C. Lee, J. Hannig, and D. Nychka (2009). Tracking of Multiple Merging and Splitting Targets with Application to Convective Systems. In press Statistica Sinica.

80. Romero Lankao, P., J. L.Tribbia and D. Nychka (2009). Testing theories to explore the drivers of cities atmospheric emissions. Ambio, 38, 236-244. 18.

81. Winter, C. L. and D. Nychka (2009) Forecasting skill of model averages. Stochastic Environmental Research and Risk Assessment, 24(5) 633-638.

82. Drignei, D., C.E. Forest, and D Nychka (2009). Parameter estimation for computationally intensive nonlinear regression with an application to climate modeling. Annals of Applied Statistics 2(4) 1217-1230.

83. Matsuo, T., D. W. Nychka, and D. Paul (2010). Multi-resolution (wavelet) based non-stationary covariance modeling for incomplete data: Smoothed Monte-Carlo EM approach. Computational Statistics and Data Analysis.

84. Li, B., D. W. Nychka and C. M. Ammann (2010). The Value of Multi-proxy Reconstruction of Past Climate. Journal of the American Statistical Association.

85. Sain S. , D. Nychka and L. Mearns (2010). Functional ANOVA and regional climate experiments: A statistical analysis of dynamic downscaling. Environmetrics 86. Oh, H-S, T. C. M. Lee, and D. W. Nychka (2010). Fast Nonparametric Quantile Regression with Arbitrary Smoothing Methods. Journal of Computational and Graphical Statistics.

### Book chapters, discussions and other edited publications

1. Bloomfield, P., Brillinger, D. R., Nychka, D. W. and Stolarski, R. (1988). “Appendix 1 Statistical Approaches to Ozone Trend Detection.” Present State of Knowledge of the Upper Atmosphere 1988: An Assessment Report NASA Reference Publication 1208, ed. Watson, R. T., NASA.

2. Bloomfield, P., Brillinger, D. R., Nychka, D. W. and Stolarski, R. (1988). “Appendix 1 Statistical Issues.” Report of the NASA-WMO Ozone Trend Panel, ed. Watson, R. T., NASA.

3. Nychka, D. (1994). Discussion to “Epidemics: Models and Data.” Journal of the Royal Statistical Society Series B.

4. Handcock, M., Nychka, D. and Meier, K. (1994). Discussion to “Kriging and Splines: An Empirical Comparison of Their Predictive Performance.” Journal of the American Statistical Association, 89, 401-403.

5. Nychka, D. and Cummins, D. (1996). Comment on: Eilers, P. and Marx, B. “Flexible Smoothing with B-splines and Penalties.” Statistical Science, 11, 104-105.

6. Bailey, B., Ellner S. and Nychka D. (1997). “Asymptotics and Applications of Local Lyapunov Exponents.” Proceedings for the Fields/CRM Workshop: Nonlinear Dynamics and Time Series: Building a Bridge Between the Natural and Statistical Sciences, American Mathematical Society, 115-133.

7. Hu, F., Hall, A. R. and Nychka, D. (2000). “A Nonparametric Approach to Stochastic Discount Factor Estimation.” Applying Kernel and Nonparametric Estimation to Economic Topics, eds. Fomby, T. and Hill, R.C., JAI Press Inc., Stamford Connecticut, 155-178.

8. Nychka, D. (2000). “Spatial Process Estimates as Smoothers.” Smoothing and Regression. Approaches, Computation and Application, ed. Schimek, M. G., Wiley, New York, 393-424.

9. Nychka, D. and Tebaldi, C. (2002), Comment on ‘Calculation of Average, Uncertainty Range and Reliability of Regional Climate Changes from AOGCM Simulations via the “Reliability Ensemble Averaging” (REA) method’ Journal of Climate, 16, 883–884.

10. Tebaldi, C. and Nychka, D. (2004) Invited discussion to “Calibrated probabilistic mesoscale weather field forecasting: the geostatistical output perturbation (GOP) method”. Journal of the American Statistical Association. 99 583–585.

11. Gilleland, E., D. Nychka and U. Schneider (2006). “Spatial models for the distribution of extremes.” In Applications of Computational Statistics in the Environmental Sciences: Hierarchical Bayes and MCMC Methods ed. J.S. Clark and A. Gelfand, Oxford University Press.

12. Surface Temperature Reconstructions for the Last 2,000 Years (2006) Committee on Surface Temperature Reconstructions for the Last 2,000 Years, National Research Council, ISBN: 0-309-66144-7

13. Data Assimilation D. Nychka and J.L. Anderson (2010) Chapter in Handbook of Spatial Statistics ed. and A Gelfand, P. Diggle, P. Guttorp and M. Fuentes . Chapman & Hall/CRC.

14. Nychka,D. J. M. Restrepo and C. Tebaldi (2008). Uncertainty in Climate Predictions. American Mathematical Society, Mathematics Awareness Month.

15. Nychka, D and Bo Li (2011). Discussion to: A Statistical Analysis of Multiple Temperature Proxies: Are Reconstructions of Surface Temperature over the last 1000 Years Reliable? McShane and Wyner. Annals of Applied Statistics

### Books

- Nychka, D., Cox, L. and Piegorsch, W. (1998). Case Studies in Environmental Statistics, Lecture Notes in Statistics, Springer Verlag, New York.
- Berliner, L.M., Nychka, D. and Hoar, T. (2000). Statistics for Understanding the Atmosphere, Springer Verlag, New York.

### Educational Materials

- Nychka, D. and Boos, D. (1993). S Lab: A series of labs for teaching statistics and data analysis. (A statistics lab manual and a set of approximately 60 S functions for teaching concepts of data analysis and probability.)
- Nychka, D. (1992). Probability and Statistics for Engineers and Scientists. North Carolina State University Video Extension Service. (A series of 70, 50 minute video taped lectures covering the principles of probability, basic statistics, regression and experimental design. )

### OpenSky

Open Access publications available through NCAR's OpenSky are available below: