**X. Dai "***Statistical Machine Learning for Complex Data Sets*" TR1187, May 2019, PhD. Thesis.

**G. Wahba and Y.Wang "***Representer Theorem*" 2019 Slightly revised version has appeared in StatsRef.

**H. H. Zhou "***Kernel Methods in the Analysis of Big and Complex Data: A Modern Statistical Challenge*" TR1185, March 2019, PhD. Thesis.

**X. Dai and ADNI "***Alzheimer's Disease Prediction Using Longitudinal and Heterogeneous Magnetic Resonance Imaging*" ArXiV October 2018.

**X. Dai and P. Chien "***Another Look at Statistical Calibration: A Non-Asymptotic Theory and Prediction-Oriented Optimality*" ArXiV September 2018.

**X. Dai and J. Huling "***Selection and Estimation Optimality in High Dimensions With the TWIN Penalty*" ArXiV June 2018.

**H. H. Zhou, Y. Xiong and V. Singh, "***Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty*" ArXiV June 2018.

**H. H. Zhou, V. Singh, S. Johnson and G. Wahba "***Statisticsl tests and identifiability conditions for pooling and analyzing multisite data sets*" PNAS 2018 115(7) 1481-1486. Supplementary information "here"

**H. H. Zhou and G. Raskutti, "***Non-parametric sparse additive auto-regressive network models.*" To Appear, IEEE Transactions on Information Theory

**G. Wahba "***Emanuel Parzen: A memorial, and a Model With the Two Kernels that He Championed*" 2018 ArXiv

**X. Dai and P. Chien, "***Minimax Optmal Rates of Estimation in Functional ANOVA Models With Derivatives*" TR 1184, September 2017, also ArXiV Winner of ASA Section on Nonparametric Statistics Student Paper Award.

**H. Zhou, Y. Zhang, V. Ithapu, S. Johnson, G. Wahba and V. Singh "***When can multi-site data sets be pooled for hypothesis tests? $\ell_2$-consistency and neurosciences applications.*" Proceedings Machine Learning Research 2017 August v. 70: 4170-4179 (ICML-179). Supplementary information "here"

**H. H. Zhou and 10 others, including G. Wahba "***Statistical Algorithem for Harmonizing Biomaker Distributions Across Different Cohorts, Sites and Assays: Applications to CSF Measurements*" Alzheimer's and Dementia July 2017 Volume 13 Issue 7 Supplement Pages P1322-1323

**G. Wahba "***Emanuel Parzen and a Tale of Two Kernels*", an Appreciation of Manny Parzen. TR 1183, February 2017.

**G. Wahba "***Historical Note: Fifty Years of Wahba's Problem*" In "Multisensor Attitude Estimation, Fundamental Concepts and Applications" 2017, H. Fourati, D. Belkhiat and K. Iniewski, Eds.

**H. Zhou and S. Ravi and V. Ithapu and S. Johnson and G. Wahba and V. Singh "***Hypothesis Testing in Unsupervised Domain Adaptation With Applications in Alzheimer's Disease*" In Advances in Neural Information Processing Systems 29 (NIPS 29). Supplementary information "here"

**J. Kong, B. Klein, R. Klein and G. Wahba "***Backward Multiple Imputation Estimation of the Conditional Lifetime Expectancy Function With Application to Censored Human Longevith Data.*" PNAS 112, 39 online before print, September, 2015. Supplementary information "here"

**J. Kong "***Topics on distance correlation, feature screening and lifetime expectancy withapplication to Beaver Dam Eye Study data*" TR 1180, June 2015. PhD. Thesis.

**T. Qin "***Statistical Justifications for Computationally Tractable Network Analysis*" TR 1179, June 2015. PhD. Thesis.

**L. Zhang, G. Wahba and M. Yuan "***Distance Shrinkage and Euclidean Embedding via Regularized Kernel Estimation*" TR 1178, September 17, 2014. Slightly revised version to appear in JRSSB.

**J. Kong, S.Wang and G. Wahba "***Using distance covariance for improved variable selection with application to genetic risk models*" TR 1177, August 30 2014. A slightly revised version of this paper has appeared in the Online version of Statistics in Medicine, 29 January 2015 under the title "Using distance covariance for improved variable selection with application to learning genetic risk models" "here"

**Z. Geng "***Variable Selection via Penalized Likelihood*" TR 1176, June 2014. PhD. Thesis.

**T. Qin and K. Rohe "***Regularized Spectral Clustering under the Degree-Corrected Stochastic Block Model*" arXiv:1309.4111, September 2013. NIPS 2013.

**K. Rohe and T. Qin "***The blessings of transitivity in sparse and stochastic networks*" arXiv:1307.2302, July 2013.

**Z. Geng, S. Wang, M. Yu, P.Monahan, V. Champion and G. Wahba "***Group variable selection via convex Log-Exp-Sum penalty with application to a breast cancer survivor study*" TR 1175, June 2013. Revision online before print, Biometrics October 2014 "here"

**G. Wahba "***Statistical Model Building, Machine Learning and the Ah-Ha Moment*" TR 1173, March 2013. Invited for "Past, Present and Future of Statistical Science" Invited by COPSS for their 50th Anniversary celebratory volume. Consists mostly of personal reminiscences. Entire volume*here**.**Errata*

**J. Kong, B. E. K. Klein, R. Klein, K. Lee and G. Wahba "***Using distance correlation and SS-ANOVA to assess associations of familial relationships, lifestyle factors, diseases and mortality*" TR 1172, September 2012. PNAS 109, 50 20352-20357, Dec 11, 2012 "here". Correction message "here"

**B. Dai "***Multivariate Bernoulli Distribution Models*" TR 1171, July 2012. PhD. Thesis.

**B. Dai, S. Ding and G. Wahba "***Multivariate Bernoulli Distribution*" TR 1170, June 2012. Now in the Anniversary issue of Bernoulli, 19(4), 2013, 1465-1483.

**K. Rohe, T. Qin and H. Fan, "***The Highest Dimensional Stochastic Blockmodel with a Regularized Estimator*" TR 1169, September 2012.

**S. Ding "***Learning Graph Structure with Parametric and Non-Parametric Models.*" TR 1168, June 2012. PhD. Thesis. Link to software is expected to appear here.

**W. Shi, G. Wahba, R. A. Irizarry, H. Corrada Bravo and S. Wright "***The Partitioned LASSO-Patternsearch Algorithm with Application to Gene Expression Data*" TR 1166r, revised version of August, 2011. Link to the pLPS algorithm "here". BMC Bioinformatics 2012 13-98 "here".

**S. Xiong, B. Dai and P. Qian "***Orthogonalizing Penalized Regression*" July, 2011. To Appear, Technometrics

**S. Ding, G. Wahba and X. Zhu. "***Learning Higher-Order Graph Structure with Features by Structure Penalty*" TR 1164, June, 2011. Accepted (22%rate) for presentation at NIPS 2011. Final version*here.*Has appeared in Advances in Neural Information Processing Systems 24.

**G. Wahba "***Dissimilarity Data in Statistical Model building and Machine Learning.*" Fifth International Congress of Chinese Mathematicians, AMS/IP Studies in Advanced Mathematics, Vol 51, 2012, 785-809. Lizhen Ji, Yat Sun Poon, Lo Yang and Shing-Tung Yao, Eds. (Expands on TR1155 and JSPI v 140, issue 12, Dec 2010, pp3580-3596)

**Ma, X. "***Penalized Regression in Reproducing Kernel Hilbert Spaces With Randomized Covariate Data.*" TR 1159, May, 2010. PhD. Thesis.

**X. Ma, B. Dai, R. Klein, B. E. K. Klein, K. Lee and G. Wahba. "***Penalized likelihood regression in reproducing kernel Hilbert spaces with randomized covariate data.*" TR1158, April 2010.

**X. Ma, G. Wahba and B. Dai "***Penalized likelihood regression in reproducing kernel Hilbert spaces with randomized covariate non-Gaussian data*" Finalist in the 2009 ASA Nonparametric Statistics Section student paper competition. In the Proceedings of JSM 2009. TR1156, September 2009.

**G. Wahba "***Encoding Dissimilarity Data for Statistical Model Building*" For the Volume in Honor of the 80th Birthday of Distinguished Professor Emmanuel Parzen, J. Statistical Planning and Inference, online version May, 2010 (formerly TR1155, September 2009.) (Has appeared, JSPI v 140, issue 12, Dec 2010, pp3580-3596)

**H. Corrada Bravo, G. Wahba, K. E. Lee, B. E. K. Klein, R. Klein and S. K. Iyengar "***Examining the Relative Influence of Familial, Genetic and Environmental Covariate Information in Flexible Risk Models*" PNAS May 19, 2009, 106, 8128-8133. Link to "In This Issue"*here*where the paper is listed. A few more details in TR1148 below.

**H. Corrada Bravo, S. Wright, K. Eng, S. Keles and G. Wahba**"*Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming*" In Proceedings of the Twelfth International Conference on Artificial Intelligence, Volume 5: AISTATS 2009, 41-48.

**H. Corrada Bravo, G. Wahba, K. E. Lee, B. E. K. Klein, R. Klein and S. K. Iyengar "***Examining the Relative Influence of Familial, Genetic and Environmental Covariate Information in Flexible Risk Models With Application to Ophthalmology Data*" TR 1148, December, 2008.

**Shi, W.**"*LASSO-Patternsearch Algorithm*" TR 1147, December, 2008. PhD. Thesis.

**Corrada Bravo, H.**"*Graph-Based Data Analysis: Tree-Structured Covariance Estimation, Prediction by Regularized Kernel Estimation and Aggregate Database Query Processing for Probabilistic Inference*" TR 1145, August, 2008. PhD. Thesis.

**K. Eng, S. Keles, and G. Wahba**"*A Linear Mixed Effects Clustering Model for Multi-Species Time Course Gene Expression Data*" TR1143, July, 2008. Six Supplementary heatmap plots and a silhouette plot are "*here*"

**H. Corrada Bravo, K. Eng, S. Keles, G. Wahba, and S. Wright**"*Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming with an Application to Phylogenetic Analysis of Gene Expression*" TR1142, July, 2008. Further information including an R interface to CPLEX can be found "*here*"

**W. Shi, G. Wahba, S. Wright, K. Lee, R. Klein and B. Klein.**"*LASSO-Patternsearch Algorithm with Applications to Ophthalmology and Genomic Data*" In Statistics and Its Interface(SII), 1(2008) 137-153. Link to the LPS algorithm "here"

**Shi, W., Lee, K., and Wahba, G.**"*Detecting Disease Causing Genes by LASSO-Patternsearch Algorithm*" BMC Proceedings 2007 1 (Suppl 1) S60.

**Cho, S.-H. and Chun, H.**"*Visualizing Abnormal Climate Changes in Central America From 1995 to 2000*" TR 1138, March, 2007. Long version of the poster in TR1128 that won first prize in Data Expo 2006.

**Wahba, G.**"*Statistical Learning in Medical Data Analysis*" TR 1136, February 21, 2007. In Handbook of Statistics: Epidemiology and Medical Statistics, C. R. Rao, J. Philip Miller and D. C. Rao, Eds. Elsevier, 679-711, 2007.

**Carew, J.**"*Statistical Methods for Magnetic Resonance Images*" TR 1133, December, 2006. PhD. Thesis.

**Wahba, G.***Comments to "Support Vector Machines With Applications" by J. M. Moguerza and A. Munoz.*In Statistical Science 2006, 21, 347-351

**J. D. Carew, C. G. Koay, G. Wahba, A. L. Alexander, M. E. Meyerand and P. J.Basser**"*The Asymptotic Behavior of the Nonlinear Estimators of the Diffusion Tensor and Tensor-Derived Quantities with Implications for Group Analysis.*" TR 1132, November, 2006. Accepted for oral presentation at the International Society for Magnetic Resonance in Medicine (ISMRM) 14th Scientific Meeting, Seattle May 2006.

**Shi, W., Wahba, G., Wright, S., Lee, K., Klein, R., and Klein, B.**"*LASSO-Patternsearch Algorithm with Application to Ophthalmalogy Data.*" TR 1131, October, 2006.

**G. Wahba.**"*A Statistician Thinks About Machine Learning (Editorial).*" In Statistica Sinica, 16 (2006) 305-306.

**Cho, S.-H. and Chun, H.**"*Visualizing Abnormal Climate Changes in Central America From 1995 to 2000 - Data Expo 2006*" TR 1128, August, 2006. Congrats to Sang-Hoon Cho and Hyonho Chun who won First Prize in the Data Expo 2006 Competition at JSM2006 for this poster.

**Lu, F.**"*Regularized Nonparametric Logistic Regression and Kernel Regularization*" TR 1124, July, 2006. PhD. Thesis.

**Lu, F., Keles, S., Lin, Y., Wright, S. and Wahba, G.**"*Kernel Regularization and Dimension Reduction*" TR 1119, April, 2006. Congrats to Fan Lu who won the "Best Student Paper Award", ASA Statistical Computing and Graphics Sections, JSM2006 for this long abstract. Fan Lu also won the International Biometric Society's Eastern North American Region (ENAR) Distinguished Student Paper Award (2006) for his contributions in Lu, Keles, Wright and Wahba (2005) below .

**Xie, X., Chung, M., and Wahba, G.**"*Magnetic Resonance Image Segmentation With Thin Plate Spline Thresholding*" TR 1105, February, 2006.

**Lu, F., Lin, Y., and Wahba, G.**"*Robust Manifold Unfolding with Kernel Regularization*" TR 1108, October, 2005.

**Xie, X.**"*Some Smoothing in Magnetic Resonance Image Analysis and A hybrid Loss for Support Vector Machine.*" TR 1110, August 2005. PhD. Thesis.

**Lu, F., Keles, S., Wright, S., and Wahba, G.***Framework for Kernel Regularization With Application to Protein Clustering.*Proceedings of the National Academy of Sciences, 102(2005) 12332-12337. Open access.

**Lu, F., Hill, G., Wahba, G., and Desiati, P.**"*Signal Probability Estimation with Penalized Likelihood Method on Weighted Data.*" TR 1106, March, 2005. Has appeared in Statistica Sinica 16, 459-470 (2006).

**Carew, J., Wahba, G., Koay, C., Wu, Y., Alexander, A. and Meyerand, M. E.**"*Automatic Classification of High Angular Resolution Diffusion Data.*" TR 1103, February, 2005. Accepted for oral presentation at the International Society for Magnetic Resonance in Medicine (ISMRM) 13th Scientific Meeting, Miami Beach May 2005.

**Leng, C.**"*Some Problems in Model Selection.*" TR 1094, July 2004. PhD. Thesis.

**Yuan, M.**"*Automatic Smoothing and Variable Selection via Regularization.*" TR 1093, July 2004. PhD. Thesis.

**Leng, C., Lin, Y., and Wahba, G.**"*A Note on the LASSO and related procedures in model selection*" TR 1091r, April, 2004 as revised December 2004. Has appeared in Statistica Sinica, 16 (4), 1273-1284 (2006).

**Hoffmann, T., Chung, M., Dalton, K., Alexander, A., Wahba, G., and Davidson, R.**"*Subpixel curvature estimation of the corpus callosum via splines and its application to autism.*" 2004. Accepted for presentation at the 10th Annual meeting of the Organization for Human Brain Mapping.

**Carew, J., Dalal, R., Wahba, G., and Fain, S.**"*Estimating Arterial Wall Shear Stress (pdf)*" TR 1088, December 2003. Part I accepted for presentation at ISMRM12, Kyoto. Student travel award to John Carew to present part I. In Proc.Intl. Soc. Mag. Reson. Med. 11, 1924 (2004) "here"

**Hill, G., Lu, F., Desiati, P., and Wahba, G.**"*Optimizing the limit setting potential of a multivariate analysis using the Bayes posterior ratio. (pdf)*" November, 2003. Has appeared in the Proceedings of PHYSTAT2003 at SLAC.

**Yuan, M, and Wahba, G.**"*Doubly Penalized Likelihood Estimator in Heteroscedastic Regression (ps)*"*(pdf)*TR 1084rr, October 2003, revised February 2004, In Statistics and Probability Letters, 69 11-20 (2004).

**Yuan, M.**"*Automatic Smoothing for Poisson Regression (ps)*"*(pdf)*TR 1083, October, 2003, has appeared in Commun. Stat. Theor. Meth. 34, 603-617, (2005).

**Wahba, G., Lin, Y., Lee, Y., Zhang, H., Nychka, D. and Wong, W.**TR 1080 "*The 2003 Wald Lectures, with discussion. (html)*"

**Wahba, G.**"*Reproducing Kernel Hilbert Spaces - Two Brief Reviews*" TR 1079, April 2003. Has appeared in the Proceedings of the 13th IFAC Symposium on System Identification, 2003, 549-559.

**Lee, Y., Wahba, G. and Ackerman, S.**"*Classification of Satellite Radiance Data by Multicategory Support Vector Machines*" TR 1075, February 2003.Congrats to Yoonkyung Lee who won the best "Student" poster at the 2003 American Meteorological Society in the Satellite Meteorology and Oceanography session, on this work.Revised version here in Journal of Atmospheric and Oceanic Technology (JTECH), 21, 159-169 (2004)

**Lin, Y., and Zhang, H.**"*Component Selection and Smoothing in Smoothing Spline Analysis of Variance Models*" TR 1072, November 2002, rev Jan 2003.

**Wahba, G.***Soft and Hard Classification by Reproducing Kernel Hilbert Space Methods.*Proceedings of the National Academy of Sciences, 102(2002) 12332-12337. Open access.

**Zhang, H.**"*Nonparametric Variable Selection and Model Building Via Likelihood Basis Pursuit*" TR 1066, September 2002. PhD. Thesis.

**Lee, Y., Lin, Y. and Wahba, G.**"*Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data*" TR 1064, September 2002.*OSU TR 714*This Sept 2003 Ohio State TR is a revision which contains further results concerning the relation of other multicategory methods to the Bayes rule. Has appeared in J. Amer. Statist. Assoc, 99, 465 (2004) 67-81. Lead paper in the Theory and Methods section.

**Lee, Y.**"*Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data*" TR 1063, September 2002. PhD. Thesis.

**Zhang, H., Wahba, G., Lin, Y., Voelker, M., Ferris, M., Klein, R. and Klein, B.***Variable Selection and Model Building via Likelihood Basis Pursuit*(ps) (pdf) TR 1059r. March 2003. Revised and expanded version of TR 1059, July, 2002. Congrats to Hao Helen Zhang who won a 2003 Laha Travel Award to present her work at JSM. Has appeared in J. Amer. Statist. Assoc. 99 (2004) 659-672

**Carew, J., Wahba, G., Xie, X., Nordheim, E., and Meyerand, M.***Optimal Spline Smoothing of fMRI Time Series by Generalized Cross-Validation*(pdf) TR 1058, June 2002. In NeuroImage 18, 950-961, 2003.

**Lee, Y. and Lee, C.-K.***Classification of Multiple Cancer Types by Multicategory Support Vector Machines Using Gene Expression Data.*(ps)*(pdf)*TR 1051, April 2002, minor revisions July 2002, has appeared in Bioinformatics, 19 (2003) 1132-1139.

**Wahba, G., Lin, Y., and Leng, C.***Penalized Log Likelihood Density Estimation via Smoothing-Spline ANOVA and ranGACV - Comments to Hansen and Kooperberg `Spline Adaptation in Extended Linear Models'*(ps) (pdf) TR 1048, December 2001, Invited Comments. In Statistical Science 17:33-37, 2002.

**Wahba, G., Lin, Y., Lee, Y. and Zhang, H.**"*Optimal Properties and Adaptive Tuning of Standard and Nonstandard Support Vector Machines*" TR 1045, October 2001. In Nonlinear Estimation and Classification, Denison, Hansen, Holmes, Mallick and Yu, eds, Springer, 125-143, 2002. (Supercedes TR 1039).

**Zhang, H., Wahba, G., Lin, Y., Voelker, M., Ferris, M., Klein, R. and Klein, B.**"*Variable Selection via Basis Pursuit for Non-Gaussian Data*" TR 1042, October 2001. In Proceedings of the ASA Joint Statistical Meetings, 2001.

**Lee, Y, Lin, Y. and Wahba, G.**"*Multicategory Support Vector Machines*" TR 1043, September, 2001. Long version of TR 1040. In Computing Science and Statistics 33, The Interface Foundation.

**Lee, Y, Lin, Y. and Wahba, G.**"*Multicategory Support Vector Machines (Preliminary Long Abstract)*" TR 1040, July 2001.

**Wahba, G., Lin, Y., Lee, Y. and Zhang, H.**"*On the Relation Between the GACV and Joachims' \xi\alpha Method for Tuning Support Vector Machines, With Extension to the Nonstandard Case*" TR 1039, June 2001.

**Wahba, G.**"*(Smoothing) Splines in Nonparametric Regression.*" TR 1024, September 2000. In Encyclopedia of Environmetrics, A. El-Shaarawi and W. Piegorsch, Eds., Wiley, 4:2099-2112, 2001.

**Lin, Y., Wahba, G., Zhang, H., and Lee, Y.**"*Statistical Properties and Adaptive Tuning of Support Vector Machines.*" TR 1022, September 2000. Has appeared in Machine Learning, 48, 115-136, 2002.

**Wahba, G.**"*An Introduction to Model Building With Reproducing Kernel Hilbert Spaces (Interface 2000 Shortcourse overheads).*" TR 1020, April 2000.

**Lin, Y., Lee, Y., and Wahba, G.**"*Support Vector Machines for Classification in Nonstandard Situations*" TR 1016, March 2000. Has appeared in Machine Learning, 46, 191-202, 2002.

**Wahba, G.**"*Generalization and Regularization in Nonlinear Learning Systems.*" Has appeared in the second edition of the*Handbook of Brain Theory and Neural Networks*Michael Arbib, Ed., The MIT PRESS, 2002, pp 470-474.

**Gao, F.**"*Iterated ranGACV: a Computational Proxy for the Comparative Kullback-Leibler Distance*" TR 1011, July 1999.

**Chiang, A., Wahba, G., Tribbia, J., and Johnson, D. R.**"*Quantitative Study of Smoothing Spline-ANOVA Based Fingerprint Methods for Attribution of Global Warming*" TR 1010, July 1999.

**Gao, F., Wahba, G., Klein, R. and Klein, B.**"*Smoothing Spline ANOVA for Multivariate Bernoulli Observations, With Application to Ophthalmology Data*" TR 1009, July 1999. Slightly revised version in J.Amer.Statist. Assoc. 96 (2001) 127-160, with discussion. "*here.*"

**Wahba, G., Lin, Y. and Zhang, H.**"*Generalized Approximate Cross Validation for Support Vector Machines, or, Another Way to Look at Margin-Like Quantities*" TR 1006, April 1999. Expanded version of TR1006 posted here February 1999. With revisions in `Advances in Large Margin Classifiers, Smola, Bartlett, Scholkopf and Schurmans, eds., MIT Press (2000), 297-309, " here."

**Gao, F.**"*Penalized Multivariate Logistic Regression With a Large Data Set*" 1999, Ph.D. Thesis.

**Wahba, G.**"*Adaptive Tuning, Four Dimensional Variational Data Assimilation, and Representers in RKHS*" TR 1000, November 1998. Has appeared in `Diagnosis of Data Assimilation Systems', Proceedings of a Workshop held at ECMWF. European Centre for Medium-Range Weather Forecasts, Reading, England, March 1999, 45-52.

**Lin, X., Wahba, G., Xiang, D., Gao, F. Klein, R. and Klein, B.**"*Smoothing Spline ANOVA Models for Large Data Sets With Bernoulli Observations and the Randomized GACV*" TR 998, September 1998. Long version of TR 997. Slightly revised version in*Ann. Statist. 28 (2000) 1570-1600*.

**Wahba, G., Lin, X., Gao, F., Xiang, D., Klein, R. and Klein, B.**"*The Bias-Variance Tradeoff and the Randomized GACV*" TR 997, Septemter 1998. In Advances in Neural Information Processing Systems 11, M. Kearns, S. Solla and D. Cohn, Eds, MIT Press (1999) pp 620-626.

**Wahba, G.**"*Comments to Chong Gu, `Model Indexing and Smoothing Parameter Selection in Nonparametric Function Estimation'*" Statistica Sinica 8, 1998, 632-638.

**Lin, X.**"*Smoothing Spline Analysis of Variance for Polychotomous Response Data*" December 1998, Ph.D. Thesis. (TR 1003)

**Wang, Y. and Wahba, G.**"*Comments to Brumback and Rice, `Smoothing Spline Models for the Analysis of Nested and Crossed Samples of Curves'*" J. Roy. Stat. Soc. B 93, 976-980 (1998).

**Wahba, G.**"*Support Vector Machines, Reproducing Kernel Hilbert Spaces and the Randomized GACV*" "*typos*" TR 984rr, July 1998. (Second revision of version of November 1997). In `Advances in Kernel Methods - Support Vector Learning', Sch\"olkopf, Burges and Smola (eds.), MIT Press 1999, 69-88.

**Xiang, D., and Wahba, G.**"*Approximate Smoothing Spline Methods for Large Data Sets in the Binary Case*" TR 982, September 1997. In the Proceedings of the 1997 ASA Joint Statistical Meetings, Biometrics Section, 94-98(1998)

**Luo, Z. , Wahba, G, and Johnson, D. R.**"*Spatial-Temporal Analysis of Temperature Using Smoothing Spline ANOVA*" J. Climate 11, 18-28 (1998).

**Luo, Z.**"*Backfitting in Smoothing Spline ANOVA*"Ann. Statist 1998, 26, 1733-1759

**Wang, Y.**"*Mixed-Effects Smoothing Spline ANOVA*" TR 967, August 1996, JRSS B, 60, 159-174 (1998).

**Wang, Y.**"*Smoothing Spline Models With Correlated Random Errors*" TR 966, August 1996, JASA 93, 341-348 (1998).

**Luo, Z.**"*Backfitting in Smoothing Spline ANOVA, With Application to Historical Global Temperature Data*" TR 964, July 1996. PhD. Thesis

**Gong, J., Wahba, G., Johnson, D. R., and Tribbia, J.**"*Adaptive Tuning of Numerical Weather Prediction Models: Simultaneous Estimation of Weighting, Smoothing and Physical Parameters*" TR 963, July 1996,*slightly revised version*Monthly Weather Review 126, 210-231 (1998).

**Xiang, D.**"*Model Fitting and Testing for Non-Gaussian Data with a Large Data Set*" TR 957, January 1996. PhD. Thesis

**Wang, Y., Wahba, G., Gu, C., Klein, R. and Klein, B.**"*Using Smoothing Spline ANOVA to Examine the Relation of Risk Factors to the Incidence and Progression of Diabetic Retinopathy*" Statistics in Medicine, 16, 1997, pp. 1357-1376.

**Xiang, D. and Wahba, G.**"*Testing the Generalized Linear Model Null Hypothesis versus "Smooth" Alternatives.*" TR 953, October 1995.

**Wahba, G. and Luo, Z.**"*Smoothing Spline ANOVA Fits for Very Large, Nearly Regular Data Sets, with Application to Historical Global Climate Data"*TR 952, October 1995.*Slightly revised version*in Annals of Numerical Mathematics 4 (1997) 579-598. (Festschrift in Honor of Ted Rivlin, C.Micchelli, Ed.)

**Luo, Z. and Wahba, G.**"*Hybrid Adaptive Splines"*TR 947, June 1995, slightly revised version has appeared in J. Amer. Statist. Assoc., 92, 1997, pp. 107-116. "*here*"

**Wang, Y.**"*Odds Ratio Estimation in Bernoulli Smoothing Spline ANOVA Model"*TR 946, April 1995, has appeared in The Statistician, 46, 1997, 49-56

**Wang, Y.**"*GRKPACK: Fitting Smoothing Spline ANOVA Models for Exponential Families.*" TR 942, January 1995. Documentation for GRKPACK. The GRKPACK code is in`~wahba/ftp1/software/grkpack.shar.gz`

**Wahba, G., Wang, Y., Gu, C., Klein, R. and Klein, B.**"*Smoothing Spline ANOVA for Exponential Families, with Application to the Wisconsin Epidemiological Study of Diabetic Retinopathy.*" May 1995, Ann. Statist. 23 (1995), 1865-1895. Expanded and slightly revised version of TR 940, December 1994. This paper was the basis for the Neyman Lecture given at the Annual Meeting of the Institute of Mathematical Statistics at Chapel Hill 1994, delivered by the first author.

**Xiang, D. and Wahba, G.**"*A Generalized Approximate Cross Validation for Smoothing Splines with Non-Gaussian Data.*" TR 930, September 1994, slightly revised version, " Statistica Sinica, 6, 1996, pp.675-692.**Wahba, G., Wang, Y., Gu, C., Klein, R. and Klein, B.**"*Structured Machine Learning for `Soft' Classification with Smoothing Spline ANOVA and Stacked Tuning, Testing and Evaluation.*" In `Advances in Neural Information Processing Systems 6, J. Cowan, G. Tesauro and J. Alspector, Eds., 1994, Morgan Kauffman, pp. 415-422.**Wahba, G.**"*Generalization and Regularization in Nonlinear Learning Systems.*" TR 921, May, 1994. In the*Handbook of Brain Theory and Neural Networks*, Michael Arbib, Ed, The MIT PRESS, 1995, pp. 426-430.**Wahba, G., Johnson, D. R., Gao, F. and Gong, J.**"*Adaptive tuning of numerical weather prediction models: Part I: randomized GCV and related methods in three and four dimensional data assimilation.*" TR 920, April 1994.*Short version*Monthly Weather Review, 123 (1995), 3358-3369, under the title `Adaptive Tuning of Numerical Weather Prediction Models: Randomized GCV in Three-and Four-Dimensional Data Assimilation.**Wang, Y. and Wahba, G.**"*Bootstrap Confidence Intervals for Smoothing Splines and their Comparison to Bayesian Confidence Intervals.*" TR 913, January 1994, slightly revised version in J. Statistical Computation and Simulation, 51 (1995) 263-279.

**Wahba, G. and Wang, Y.**"*Behavior near zero of the distribution of GCV smoothing parameter estimates.*" TR 910, December 1993. Has appeared in Statistics and Probability Letters, 25 (1995) 105-111.**Gao, F.**"*On Combining Data from Multiple Sources with Unknown Relative Weights.*" TR 894 (Rev), February 1993. Revised version appears in Commun. Statist. T heor. Meth., 23, 1994, pp. 1665-1698, as `Fitting smoothing splines to data from multiple sources with unknown relative weights'**Wahba, G., Gu, C., Wang, Y. and Chappell, R.**"*Soft Classification, a.k.a. Risk Estimation, via Penalized Log Likelihood and Smoothing Spline Analysis of Variance.*" TR 899, January 1993. (Some typographical errors corrected on October 11, 1993.) In `Computational Learning Theory and Natural Learning Systems', Volume 3, T. Petsche, Ed, MIT Press pp. 127-158. Reprinted in `The Mathematics of Generalization', D. Wolpert, Ed., Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. XX, Addison-Wesley, pp. 329-360, 1995.**Gu, C., and Wahba, G.**""J. Computational and Graphical Statistics 2, 1993, pp. 97-117.*Smoothing Spline ANOVA with Componennt-Wise Bayesian `Confidence Intervals'***Gu, C., and Wahba, G.**""JRSS B 55, 1993, 353-368.*Semiparametric Analysis of Variance with Tensor Product Thin Plate Splines*