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Papers

in chronological order. Topics are indicated by tags.
CV with complete list
[NP] nonparametric Bayes
[DEC] optimal design and decision problems
[CT] clinical trial design
[GR] graphical model
[BIO] biostat and bioinfo

2013

  1. [NP] Lee, J., Quintana, F., Müller, P. and Trippa, L. (2013), ``Defining Predictive Probability Functions for Species Sampling Models,'' Statistical Science, to appear. tech report (pdf)
  2. [GR] Mitra, R., Müller, P., Liang, S., Yue, L, and Ji, Y. (2013), ``A Bayesian Graphical Model for Chip-Seq Data on Histone Modifications,'' Journal of the American Statistical Association, to appear. tech report (pdf)
  3. [DEC] León-Novelo, L., Müller, P., Do, K-A., Arap, W., Sun, J. and Pasqualini, R. (2012), ``Semi-Parametric Bayesian Inference for Phage Display Data,'' Biometrics, to appear, DOI: 10.1111/j.1541-0420.2012.01817.x. tech report (pdf)
  4. [DEC] Rossell, D. and Müller, P. (2013) ``Sequential sample sizes for high-throughput hypothesis testing experiments,'' Biostatistics, 14, 75-86. tech report (pdf)

  5. [BIO] Müller, P. (2013), ``Bayesian Models in Biostatistics and Medicine'', in Bayesian Theory and Applications, P. Damien, P. Dellaportas, N. Polson and D. Stephens (eds), p. 557-575, Oxford University Press.
  6. [DEC] Laud, P., Sivaganesan, S. and Müller, P. (2013), ``Subgroup Analysis," in P. Damien, P. Dellaportas, N. Polson and D. Stephens (eds), p. 576-592, Oxford University Press.
  7. [BIO] Mitra, R., Müller, P., Ji, Y. (2013), ``Bayesian Model-Based Approaches for Solexa Sequencing Data,'' in Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data, Do, K.A., Qin, Z. and Vannucci, M. (editors), Cambridge University Press (in press).
  8. [CT] Jiang, F., Lee, J.J., and Müller, P. (2013) ``A Bayesian decision-theoretic sequential--response adaptive randomization design,'' Statistics in Medicine, to appear, DOI: 10.1002/sim.5735.
  9. [NP] Alejandro Cruz-Marcelo, Gary L. Rosner, Peter Müller, Clinton F. Stewart (2013), ``Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models,'' Journal of Statistical Theory and Practice, to appear.

2012

  1. [DEC] León-Novelo, L., Müller, P., Do, K-A., Arap, W., Sun, J. and Pasqualini, R. (2012), ``Bayesian Decision Theoretic Multiple Comparison Procedures: An Application to Phage Display Data'', Biometrical Journal, to aeppar, DOI: 10.1002/bimj.201200051. tech report (pdf)
  2. [GR] Telesca, D., Müller, P, Parmigiani, G., and Freedman, R. (2012), ``Modeling Dependent Gene Expression'', Annals of Applied Statistics, 6, 542-560.
  3. [GR] Telesca, D., Müller, P, Kornblau, S., and Ji, Y. (2012), ``Modeling Protein Expression and Protein Signaling Pathways'', Journal of the American Statistical Association, 107, 1372-1384.
  4. [NP] Berger, J., Jefferys, W., and Müller, P. (2012), ``Bayesian Nonparametric Shrinkage Applied to Cepheid Star Oscillations,'' Statistical Science, 27, 3-10.
  5. [CT] Morita, S., Thall, P. and Müller, P. (2012), ``Prior Effective Sample Size in Conditionally Independent Hierarchical Models,'' Bayesian Analysis, 7, 591 - 614.
  6. [NP] Leon-Novelo, L., Bekele, B.N., Müller, P., Quintana, F. and Wathen, K., (2012), ``Borrowing Strength with Non-Exchangeable Priors over Subpopulations'', Biometrics, 68 (2), 550-558, PMID 22040065. tech report (pdf)
  7. [NP] Nieto-Barajas, L., Müller, P., Ji, Y., Lu, Y. and Mills, G. (2012), ``Time Series Dependent Dirichlet Process.'' Biometrics, 68, 859--868. tech report (pdf)
  8. [CT] Trippa, L, Rosner, G., and Müller, P. (2012), ``Bayesian Enrichment Strategies for Randomized Discontinuation Trials'', with discussion, Biometrics, 68, 203--211. tech report (pdf)
  9. [NP] Nieto-Barajas, L. and Müller, P. (2012), ``Rubbery Polya Tree.'' Scandinavian Journal of Statistics, 39, 166 -- 184. tech report (pdf)
  10. [BIO] Ji, Y., Mitra, R., Quintana, F., Müller, P., Jara, A., Liu, P., Lu, Y. and Liang, S. (2012), ``BM-BC: A Bayesian method of base calling for Solexa sequence data'' BMC Bioinformatics, 13:S6, doi:10.1186/1471-2105-13-S13-S6 tech report (pdf)
  11. [BIO] Guoshuai Cai, Hua Li, Yue Lu, Xuelin Huang, Juhee Lee, Peter Müller, Yuan Ji and Shoudan Liang (2012), ``Accuracy of RNA-Seq and its dependence on sequencing depth,'' BMC Bioinformatics, 13(Suppl 13):S5 doi:10.1186/1471-2105-13-S13-S5.
  12. [NP] Di Lucca, M.A., Guglielmi, A., Müller, P., and Quintana, F. (2012), ``Bayesian autoregressive nonparametric models'', Bayesian Analysis, 7, 771-796. tech report (pdf)

2011

  1. [BIO] Lee, J., Ji, Y., Liang, S., Cai, G., and Müller, P. (2011), ``On Differential Gene Expression Using RNA-Seq Data'', Cancer Informatics, 10, 205-215.
  2. [NP] Trippa, L, Müller, P. and Johnson, W. (2011), ``The Multivariate Beta Process and an Extension of the Polya Tree Model,'' Biometrika, 98 (1), 17-34, doi:10.1093/biomet/asq072
  3. [NP] Müller, P., Quintana, F, and Rosner, G. (2011), ``A product partition model with regression on covariates'', Journal of Computational and Graphical Statistics, Mar 2011, 20(1): 260-278, PMC3090756. tech report (pdf)
  4. [DEC] Sivaganesan, S., Laud, P. and Müller, P. (2011), ``A Bayesian Subgroup Analysis with a Zero-Enriched Polya Urn Scheme.'' , Statistics in Medicine, 30, 312--323, DOI: 10.1002/sim.4108.
  5. [NP] Jara, A., Hanson, T., Quintana, F., Müller, P., and Rosner, G. (2011) ``DPpackage: Bayesian Non- and Semi-parametric Modelling in R'', Journal of Statistical Software, 40 (5). tech report (pdf)
  6. [NP] Müller, P., Do, K.-A., Bandyopadhyay, R., and Baggerly, K. (2011), ``A Bayesian mixture model for protein biomarker discovery''. In Bayesian Modeling in Bioinformatics, Dey, D.K. , Ghosh, S., and Mallick, B. (Eds), Chapman & Hall / CRC press, pp. 343-364.

2010

  1. [NP] Yang, Y., Müller, P. and Rosner, G. (2010) ``Semiparametric Bayesian Inference for Repeated Fractional Measurement Data.'' Chilean Journal of Statistics, 1, 1: 59-74.
  2. [DEC] Harvey, C., Liechty, J., Liechty, M., and Müller, P. (2010), ``Portfolio Selection with Higher Moments.'' Quantitative Finance, 10 (5), 469 - 485.
  3. [NP] Li, Y., Müller, P. and Lin, X. (2011), ``Center-Adjusted Inference for a Nonparametric Bayesian Random Effect Distribution.'' Statistica Sinica, 21 (3), 1201-23.
  4. [BIO] Morita, S., Thall, P. and Müller, P. (2010), Evaluating the Impact of Prior Assumptions in Bayesian Biostatistics Statistics in Biosciences, 2(1):1-17, PMCID: PMC2910452
  5. [NP] Chen, Y.,A., Almeida, J.S., Richards, A.J., Müller, P., Carroll, R.J., and Roherer, B. (2010), ``A nonparametric approach to detect local correlation in gene expression.'' Journal of Graphical and Computational Statistics, 19, 552-568.
  6. [CT] Leon-Novelo, L.G, Zhou, X, Bekele, B., and Müller, P. (2010), ``Assessing Toxicities in a Clinical Trial: Bayesian Inference for Ordinal Data Nested within Categories'' Biometrics, 66, 966-74.
  7. [NP] Müller, P. and Quintana, F. (2010), ``Random Partition Models with Regression on Covariates'', Journal of Statistical Inference and Planning, 140 (10), 2801-2808, doi:10.1016/j.jspi.2010.03.002 tech report
  8. [DEC] Müller, P, Sivaganesan, S. and Laud, P.W. (2010), "A Bayes Rule for Subgroup Reporting", in Frontiers of Statistical Decision Making and Bayesian Analysis, M.-H. Chen, D.K. Dey, P. Müller, D. Sun and K. Ye (eds.), pp. 277 - 284.
  9. [MCMC] Liechty, M.W., Liechty, J.C., and Müller, P. (2010), "MCMC for contrained parameter and sample spaces", in Frontiers of Statistical Decision Making and Bayesian Analysis, M.-H. Chen, D.K. Dey, P. Müller, D. Sun and K. Ye (eds.), pp. 538-546.

2009

  1. [NP] Guindani, M., Zhang, S. and Müller, P. (2009), ``A Bayesian Discovery Procedure,'' Journal of the Royal Statistical Society, Series B, 71, 905-925.
  2. [NP] Zhang, S., Müller, P., and Do, K.-A. (2010), ``A Bayesian Semiparametric Method for Jointly Modeling a Primary Endpoint and Longitudinal Measurements.'' Biometrics, 66, 435-443. DOI: 10.1111/j.1541-0420.2009.01276.x (on-line advance publication).
  3. [NP] Li, Y., Lin, X., and Müller, P. (2010), ``Bayesian inference in semiparametric mixed models for longitudinal data,'' Biometrics, 66 (1), 70-78, DOI: 10.1111/j.1541-0420.2009.01227.x.
  4. [MCMC] Liechty, M.W., Liechty, J.C., and Müller, P. (2009), ``The Shadow Prior'', Journal of Computational and Graphical Statistics, 18, 368-383.
  5. [NP] De Iorio, M., Johnson, W., Müller, P., and Rosner, G. (2009). "A DDP Model for Survival Regression", Biometrics, 65, 762-71.

2008

  1. [CT] Sivaganesan, S., Laud, P.W. and Müller, P. (2008), A Bayesian Subgroup Analysis with a Zero-Enriched Polya Urn Scheme. tech report
  2. [NP] Y. Li, X. Lin and P. Müller. Bayesian inference in semiparametric mixed models for longitudinal data. Biometrics, in press. tech report ; supporting materials
  3. [NP] Lee, J., Quintana, F., Müller, P. and Trippa, L. (2008) "Defining Predictive Probability Functions for Species Sampling Models". Technical report (pdf)
  4. [NP] Quintana, F., Müller, P., Rosner, G. and Relling, M.V. (2008) ``A Semiparametric Bayesian Model for Repeated Repeated Binary Outcomes'', Applied Statistics, 57, 419--431. Technical report (pdf)
  5. [NP] DeIorio, M., Johnson, W., Müller, P., and Rosner, G. (2008). "A DDP Model for Survival Regression", Biometrics, (to appear). Technical report (pdf)
  6. [NP] Quintana, F., Müller, P., Rosner, G. and Munsell, M. (2008), ``Semi-parametric Bayesian Inference for Multi-Season Baseball Data'', Bayesian Analysis, 3, 317-338. paper
  7. Polson, N., Stroud, J., and Müller, P. (2008), ``Practical Filtering with Sequential Parameter Learning.'' JRSS B, 70, 413-28. Technical report (pdf)
  8. [CT] Ding, M., Rosner, G., and Müller, P. (2008), ``Bayesian Optimal Design for Phase II Screening Trials''. Biometrics, 64, 886--894. Technical report (pdf)
  9. Inoue, L., Etzioni, R., Morrell, C., and Müller, P. (2008), ``Modeling Disease Progression with Longitudinal Markers.'' Journal of the American Statistical Association, 103, 259-270.
  10. [CT] Morita, S., Thall, P.F., and Müller, P. (2008), ``Determining the Effective Sample Size of a Parametric Prior'' Biometrics, 64, 595--602. Technical report (pdf)
  11. [NP] Navarrete, C., Quintana, F.A. and Müller, P. (2008), ``Some Issues on Nonparametric Bayesian Modeling Using Species Sampling Models'', Statistical Modeling: International Journal, 8, 3--21. Technical report (pdf)
  12. [NP] Müller, P. and Quintana, F. (2008), ``More Nonparametric Bayesian Models for Biostatistics'', in Bayesian Nonparametrics, Hjort, N., Holmes, C., Müller, P. and Walker, S. (eds.), Cambridge University Press, (to appear).
  13. [NP] Müller, P., Quintana, F, and Rosner, G. (2008), ``Bayesian Clustering with Regression''. Technical report (pdf)
  14. [DEC] Guindani, M., Zhang, S. and Müller, P. (2008), ``A Bayesian Discovery Procedure.'' Technical report (pdf)
  15. Liechty, M.W., Liechty, J.C., and Müller, P. (2008), ``The Shadow Prior'', JCGS , to appear.

2007

  1. [NP] Zhang, S., Müller, P., and Do, K.-A. (2007), ``A Bayesian Semiparametric Method for Jointly Modeling a Primary Endpoint and Longitudinal Measurements.'' Technical report (pdf)
  2. Lopes, H.F., Ravishanker, N., and Müller, P. (2007), ``Bayesian Computational Methods in Biomedical Research'', in Computational Methods in Biomedical Research (eds. R. Khattree and D.N. Naik), Marcel Dekker/Francis & Taylor, to appear.
  3. [NP] De la Cruz-Mesia, Quintana, F., and Müller, P. (2007), ``Semiparametric Bayesian Classification with Longitudinal Markers.'' Applied Statistics, 56, 119-137. Technical report (pdf)
  4. [NP] Zhang, S. Shih, Y.-C., and Müller, P. (2007). "A Spatially-adjusted Bayesian Additive Regression Tree Model to Merge Two Datasets", Bayesian Analysis, 3, 611-34. paper (pdf)
  5. [CT] Rossell, D., Müller, P. and Rosner, G. (2007), ``Screening Designs for Drug Development.'' Biostatistics, 8, 595--608. Technical report (pdf)
  6. [DEC] Müller, P., Parmigiani, G., and Rice, K. (2007), ``FDR and Bayesian Multiple Comparisons Rules'' in Bayesian Statistics 8, J.M. Bernardo, S. Bayarri, J.O. Berger, , A.P. Dawid, D. Heckerman, A.F.M. Smith, and M. West (eds.), Oxford University Press (to appear). Technical report (pdf)
  7. [NP] Müller, P., Quintana, F., and Rosner, G. (2007), ``Semiparametric Bayesian Inference for Multilevel Repeated Measurement Data'', Biometrics, 63, 280--289. Technical report (pdf)

2006

  1. [CT] Müller, P., Berry, D.A., Grieve, A.P., and Krams, M. (2006). ``A Bayesian Decision-Theoretic Dose Finding Trial'', Decision Analysis, 3, 197-207. Technical report (pdf)
  2. [CT] Müller, P., Berry, D., Grieve, A., Smith, M., and Krams, M. (2006). ``Simulation-Based Sequential Bayesian Design'' Journal of Statistical Planning and Inference, 137, 3140--50. Technical report (pdf)
  3. Swartz, M., Kimmel, M., Müller, P., and Amos, C. (2006), ``Stochastic Search Gene Suggestion: A Bayesian Hierarchical Model for Gene Mapping,'' Biometrics, 62, 495--503.
  4. [DEC] Müller, P., Robert, C., and Rousseau, J. (2006), ``Sample Size Choice for Microarray Experiments'', in Bayesian Inference for Gene Expression and Proteomics, Do, K.-A., Müller, P., and Vannucci, M. (eds.), Cambridge University Press. Technical report (pdf)
  5. [NP] Guindani, M., Do, K.-A., Müller, P., and Morris, J. (2006), ``Bayesian Mixture Models for Gene Expression and Protein Profiles'' in Bayesian Inference for Gene Expression and Proteomics, Do, K.-A., Müller, P., and Vannucci, M. (eds.), Cambridge University Press. Technical report (pdf)
  6. [CT] Parke, T., Krams, M., Müller, P., and Berry, D. (2006), ``Efficient Dose-Response Finding Strategies for Acute Neuroemergency Treatments'', in Handbook of Neuroemergency Clinical Trials, eds. W.M. Alves and B.E. Skolnick, Chapter 9, Elsevier, San Diego.
  7. [NP] Müller, P., and Rosner, G. (2006), ``Semi-Parametric Bayesian Models for Population Pharmacokinetics and Pharmacodynamics.'' in Bayesian Statistics and Its Applications, edited by S.K. Upadhyay, Umesh Singh and Dipak K. Dey, Anamaya Publishers, New Delhi.

2005

  1. [NP] Do, K-A., Müller, P., and Tang, F. (2005). ``A Bayesian Mixture Model for Differential Gene Expression.'' Applied Statistics, 54 (3), 627-644. (pdf)
  2. [NP] Müller, P., Rosner, G., DeIorio, M., and MacEachern, S. (2005). ``A Nonparametric Bayesian Model for Inference in Related Studies.'' Applied Statistics , 54 (3), 611-626. (pdf)
  3. [NP] Menchero, A., Montes Diez, R., Rios Insua, D. and Müller, P. (2005), ``Bayesian analysis of non-linear autoregression models based on neural networks,'' Neural Computation, 17, 453--485. (pdf)

2004

  1. [NP] Kottas, A., Müller, P. and Quintana, F. (2004), ``Nonparametric Bayesian modeling for multivariate ordinal data.'' JCGS, 13, 213-231. (pdf)
  2. [CT] Christen, J.A., Müller, P., Wathen, K., and Wolf, J. (2004). ``A Bayesian Randomized Clinical Trial: A Decision Theoretic Sequential Design'', Canadian J Stat, 32(4), 387--402. (pdf)
  3. [DEC] Quintana, F., and Müller, P. (2004). ``Optimal Sampling for Repeated Binary Measurements,'' Canadian J Stat, 32, 73--84.
  4. [DEC] Müller, P., Sanso, B., and DeIorio, M. (2004). ``Optimal Bayesian Design by Inhomogeneous Markov Chain Simulation.'' JASA, 99(467), 788-798. (pdf)
  5. [NP] De Iorio, M., Müller, P., Rosner, G., and Maceachern, S. (2004). ``An ANOVA Model for Dependent Random Measures,'' JASA, 99(465), 205--215. (pdf)
  6. [DEC] Müller, P., Parmigiani, G., Robert, C., and Rousseau, J. (2004). ``Optimal Sample Size for Multiple Testing: the Case of Gene Expression Microarrays.'', JASA, 99(468), 990-1001. (pdf)
  7. [NP] Müller, P., Quintana, F. and Rosner, G. (2004). ``Hierarchical Meta-Analysis over Related Non-parametric Bayesian Models.'' JRSS B, 66, 735--749. (pdf)
  8. [NP] Müller, P., and Quintana, F. (2004). ``Nonparametric Bayesian Data Analysis,'' Statistical Science, 19, 95--110. (pdf)
  9. Liechty, J., Liechty, M., and Müller, P. (2004). ``Bayesian Correlation Estimation,'' Biometrika, 91, 1--14. (pdf)
  10. [NP] Quintana, F., and Müller, P. (2004). ``Nonparametric Bayesian Assessment of the Order of Dependence for Binary Sequences.'' Journal of Computational and Graphical Statistics, 13, 213--231.

2003

  1. Stroud, J., Müller, P., and Polson, N. (2003). ``Nonlinear State-Space Models with State-Dependent Variance Functions.'' Journal of the American Statistical Association, 98, 377-386.
  2. Freitas Lopes, H., Müller, P., and Rosner, G. (2003). ``Meta-Analysis for Longitudinal Data Models using Multivariate Mixture Priors.'' Biometrics, 59, 66-75.
  3. Barnes, T.G., Jefferys, W.H., Berger, J.O., Müller, P. Orr, K., and Rodriquez, R. (2003). ``A Bayesian Analysis of the Cepheid Distance Scale.'' Astrophysics Journal, 592, 539-554.
  4. [CT] Thall, P., Millikan, R., Müller, P., and Lee, S-J. (2003). ``Dose-Finding with two agents in phase I oncology trials.'' Biometrics, 59 (3), 487.
  5. Calder, C., Lavine, M., Müller, P., and Clark, J. (2003). ``Incorporating Multiple Sources of Stochasticity into Dynamic Population Models.'' Ecology, 84(6), 1395--1402.

2001

  1. [NP] Müller, P., Rosner, G, Inoue, L., and Dewhirst, M.W. (2001). ``A Bayesian Model for Detecting Changes in Nonlinear Profiles.'' Journal of the American Statistical Association , 96,1215-1222.
  2. Stroud, J., Müller, P., and Sanso, B. (2001). ``Dynamic Models For Spatio-Temporal Data.'' Journal of the Royal Statistical Society, Series B, 63, 673-689.
  3. [DEC] Stroud, J.R., Müller, P. and Rosner G.L. (2001). ``Optimal Sampling Times in Population Pharmacokinetic Studies,'' Applied Statistics, 50, 345-359.

2000

  1. [CT] Berry, D.A., Müller, P. Grieve, A.P, Smith, M., Parke, T., Blazek, R., Mitchard, N., and Krams, M. (2000). ``Adaptive Bayesian Designs for Dose-Ranging Drug Trials,'' in Case Studies in Bayesian Statistics V , pp. 99-182 (C. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West, eds.), Springer-Verlag, New York.
  2. [NP] MacEachern, S. and Müller, P. (2000). ``Efficient MCMC Schemes for Robust Model Extensions using Encompassing Dirichelt Process Mixture Models,'' in Robust Bayesian Analysis, F. Ruggeri and D. Rios Insua (eds.), Springer-Verlag. (pdf)

1999

  1. [DEC] Bielza, C., Müller, P., and Rios Insua, D. (1999). ``Monte Carlo Methods for Decision Analysis with Applications to Influence Diagrams,'' Management Science, 45 (7), 995-1007. (pdf)
  2. [DEC] Müller, P. (1999). ``Simulation Based Optimal Design,'' in Bayesian Statistics 6, J.O. Berger, J.M. Bernardo, A.P. Dawid and A.F.M. Smith (eds.), pp. 459--474, Oxford University Press. (pdf)
  3. Müller, P., Parmigiani, G., Schildkraut, J. and Tardella, L. (1999). ``A Bayesian Hierarchical Approach for Combining Case-control and Prospective Studies,'' Biometrics, 55, 258--266.
  4. [NP] Müller, P., and Vidakovic, B. (1999). ``Bayesian Inference with Wavelets: Density Estimation,'' Journal of Computational and Graphical Statistics, 7, 456-468.
  5. [NP] Müller, P. and Vidakovic, B. (1999). ``MCMC Methods in Wavelet Shrinkage: Non-Equally Spaced Regression, Density and Spectral Density Estimation,'' in Bayesian Inference in Wavelet-Based Models (P. Müller and B. Vidakovic, eds.), pp. 187--202, Springer-Verlag, New York.
  6. Palmer, J.L. and Müller, P. (1999). ``Population Models for Hematologic Data'', in Case Studies in Bayesian Statistics IV (C. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West, eds.), Springer-Verlag, New York. 355--366.
  7. Parmigiani, G., Berry, D., Iversen, E., Müller, P., Schildkraut, J. and Winer, E.P. (1999). ``Modeling Risk of breast cancer and decisions about genetic testing,'' in Case Studies in Bayesian Statistics IV (C. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West, eds.), Springer-Verlag, New York. 133--204.
  8. [DEC] Sanso, B. and Müller, P. (1999). ``Redesigning a Network of Rainfall Stations,'' in Case Studies in Bayesian Statistics IV (C. Gatsonis, R. E. Kass, B. Carlin, A. Carriquiry, A. Gelman, I. Verdinelli, and M. West, eds.), Springer-Verlag, New York. 383--394. (pdf)
  9. [NP] Vidakovic, B. and Müller, P. (1999). ``An Introduction to Wavelets,'' in Bayesian Inference in Wavelet-Based Models (P. Müller and B. Vidakovic, eds.), pp. 1--18, Springer-Verlag, New York. (pdf)

Note, the German ü in my name is transcribed in English as "ue" -- either is fine with me ☺ (to avoid confusion, i always use ü).

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