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A2 : Effiziente Modellbildung durch optimale Versuchsplanung

 

  • Antille, G., Dette, H. und Weinberg, A. (2003), “A note on optimal designs in weighted polynomial regression for the classical efficiency functions”, Journal of Statistical Planning and Inference, 113(1), 285-292.
  • Bailey, R.A. und Kunert, J. (2005), "On optimal cross-over designs when carry-over effects are proportional to direct effects", erscheint in: Biometrika.
  • Biedermann, S. und Dette, H. (2005), “Numerical construction of parameter maximin D-optimal designs for binary response models”, South African Statistical Journal, 39, 221-255.
  • Biedermann, S., Dette, H. und Zhu, W. (2005a), “Optimal designs for dose-response models with restricted design spaces”, erscheint in: Journal of the American Statistical Association.
  • Biedermann, S., Dette, H. und Zhu, W. (2005b), “Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals”, eingereicht (Journal of Statistical Planning and Inference).
  • Biedermann, S., Dette, H., Zhu, W. (2005c), “Compound Optimal Designs for Percentile Estimation in Dose-Response Models with Restricted Design Intervals”, in: Proceedings of the 5th St. Petersburg Workshop on Simulation. Eds.: S.M. Ermakov, V.B. Melas und A.N. Pepelyshev), 143-148.
  • Biedermann, S., Dette, H. und Pepelyshev, A. (2005a), “Optimal Discrimination Designs for Exponential Regression Models”, eingereicht (Journal of Statistical Planning and Inference).
  • Biedermann, S., Dette, H. und Pepelyshev, A. (2005b), “Some robust design strategies for percentile estimation in binary response models”, in Revision (Canadian Journal of Statistics).
  • Biedermann, S., Dette, H. und Pepelyshev, A. (2004), “Maximin optimal designs for a compartmental model”, Recent Advances in Model Orientated Data Analysis, Physica Verlag, 41-49.
  • Biedermann, S. und Dette, H. (2003a), “Robust and efficient design for the Michaelis-Menten model“, Journal of the American Statistical Association, 98, 679-686.
  • Biedermann, S. und Dette, H. (2003b), “A note on Bayesian and Maximin D-optimal designs in weighted polynomial regression”, Mathematical methods of Statistics, 12(3), 358-370.
  • Braess, D. und Dette, H. (2005), “On the number of support points of maximin and Bayesian D-optimal designs in nonlinear regression models”, in Revision (Annals of Statistics).
  • Dette, H., Haines, L. und Imhof, L. (2005a), “Bayesian and maximin optimal designs for Heteroscedastic regression models”, erscheint in: Canadian Journal of Statistics.
  • Dette, H., Haines, L. und Imhof, L. (2005b), “Maximin and Bayesian optimal designs for linear and non-linear regression models”, eingereicht (Statistica Sinica).
  • Dette, H., Kunert, J. und Pepelyshev, A. (2005), “On optimal designs for linear regression with correlated errors and analysis by weighted least squares”, eingereicht.
  • Dette, H. und Melas, V.B. (2005), “A note on some extremal problems for trigonometric polynomials”, eingereicht (Journal of Approximation Theory).
  • Dette, H., Melas, V.B. und Schpilev, P. (2005), “Optimal designs for estimating the coefficients of the lower frequencies in trigonometric regression models”, eingereicht (Annals of Statistics).
  • Dette, H. und Pepelyshev, A. (2005), “Efficient experimental designs for sigmoidal growth models”, eingereicht (Journal of Statistical Planning and Inference).
  • Dette, H. und Kwiecien, R. (2005), “Finite sample performance of sequential designs for model identification”, Journal of Statistical Computation and Simulation, 75, 477-495.
  • Dette, H., Wong, W.K. und Zhu, W. (2005), “On the equivalence of optimality criteria for the Placebo-Treatment problem”, “Statistics & Probability Letters”, 74, 337-346.
  • Dette, H., Martinez Lopez, I. , Ortiz Rodriguez, I. und Pepelyshev, A. (2005), “Efficient design of experiment for exponential regression models”, erscheint in: Journal of Statistical Planning and Inference.
  • Dette, H., Melas, V.B. und Pepelyshev, A. (2005a), “Locally E-optimal designs for exponential regression models”, erscheint in: Annals of the Institute of Statistical Mathematics .
  • Dette, H., Melas, V.B. und Pepelyshev, A. (2005b), “Optimal designs for 3D shape analysis with spherical harmonic descriptors”, erscheint in: Annals of Statistics.
  • Dette, H., Melas, V.B., Pepelyshev, A. und Strigul, N. (2005), “Design of experiments for Monod model – robust and efficient designs”, Journal of Theoretical Biology, 234, 537-550.
  • Dette, H., Melas, V.B. und Wong, W.K. (2005a), “Locally D-optimal designs for exponential regression”, erscheint in: Statistica Sinica.
  • Dette, H., Melas, V.B. und Wong, W.K. (2005b), “Optimal designs for goodness-of-fit of the Michaelis-Menten enzyme kinetic function”, erscheint in: Journal of the American Statistical Association.
  • Dette, H. und Studden, W.J. (2005), “A note on the maximization of matrix valued Hankel determinants with applications”, erscheint in: Journal of Computational and Applied Mathematics.
  • Dette, H. (2004), “On robust and efficient designs for risk estimation in epidemiologic studies”, Scandinavian Journal of Statistics, 31(3), 319-331.
  • Dette, H., Melas, V. und Pepelyshev, A. (2004a), “Optimal designs for estimating individual coefficients in polynomial regression – a functional approach”, Journal of Statistical Planning and Inference, 118(1-2), 201-219.
  • Dette, H., Melas, V. und Pepelyshev, A. (2004b), “Optimal designs for a class of nonlinear regression models”, Annals of Statistics, 32(5), 2142-2167.
  • Dette, H. und Melas, V. (2003), “Optimal designs for estimating individual coefficients in Fourier regression models”, Annals of Statistics, 31(5), 1669-1692.
  • Dette, H., V. Melas und A. Pepelyshev (2003), “Standardized maximin E-optimal designs for the Michaelis-Menten model”, Statistica Sinica, 13(4), 1147-1163.
  • Dette, H., Melas, V., Pepelyshev, A. und Strigul, N. (2003), “Efficient design of experiment in the Monod model”, Journal of the Royal Statistical Society, Series B, 65(3), 725-742.
  • Dette, H., Melas, V. und Biedermann, S. (2002), “A functional-algebraic determination of D-optimal designs for trigonometric regression models on a partial circle”, Statistics & Probability Letters, 58(4), 389-397.
  • Dette, H., Melas, V. und Pepelyshev, A. (2002), “ D-optimal designs for trigonometric regression models on a partial circle”, Annals of the Institute of Statistical Mathematics , 54(4), 945-959.
  • Dette, H. und Biedermann, S. (2001a), "Optimal Designs for Testing the Functional Form of a Regression via Nonparametric Estimation Techniques", Statistics & probability Letters, 52, 215-224
  • Dette, H. und Biedermann, S. (2001b), "Minimax Optical Designs for Nonparametric Regression - Two Further Optimality Properties of the Uniform Distribution", Recent Advances in Model Orientated Data Analysis, 13-20
  • Dette, H. und Franke, T. (2001), “Robust designs for polynomial regression by maximizing a minimum of D- and D 1-efficiencies”, Annals of Statistics, 29(4), 1024-1049.
  • Dette, H., Song, D. und Wong, W.K. (2001), “Robustness properties of minimally-supported Bayesian D-optimal designs for heteroscedastic models”, Canadian Journal of Statistics, 29(4), 633 –647.
  • Dette, H. und Franke, T. (2000), "Constrained D- and D1 Optimal Design for Polynomial Regression, Annals of Statistics, 28, 1702-1727
  • Dette, H. und Wong, W.K. (1999a), "Optimal designs for modeling response's variance as a function of the mean", erscheint in: Biometrics.
  • Dette, H. und Wong, W.K. (1999b), "E-optimal designs for the Michaelis-Menten model", Statistics & Probability Letters, 44, 405-408.
  • Dette, H. und Huang M.-N. (1999), "Convex optimal designs for compound polynomial extrapolation", erscheint in: Annals of the Institute of Statistical Mathematics .
  • Dette, H. (1998), "Some applications of canonical moments", in: Fourier regression models, New Developments and Applications in Experimental Design, N. Flournoy, W.F. Rosenberger und W.K. Wong, (eds.), Inst. of Math. Statistics, Hayward , 175-185.
  • Dette, H. und Haller, G. (1998), "Optimal discriminating designs for Fourier regression", Annals of Statistics, 26, 1496-1521.
  • Dette, H. und Sahm, M. (1998a), "E-Optimal designs for the double exponential model":, in: Recent Advances in Model Orientated Data Analysis and experimental Design, A.C. Atkinson, L. Pronzato und H.P. Wynn (eds.), Physica Verlag, Heidelberg, 11-20.
  • Dette, H. und Sahm, M. (1998b), "Minimax designs in nonlinear regression models", Statistica Sinica, 8, 1249-1264.
  • Dette, H. und Wong, W.K. (1998), "Bayesian D-optimal designs on a fixed number of design points for heteroscedastic polynomial models", Biometrika, 85, 869-882.
  • Dette, H. (1997a), "Designing of experiments with respect to "standardized" optimality criteria", Journal of the Royal Statistical Society B, 59, 97-110.
  • Dette, H. (1997b), "A note on the uniform distribution on the arcsin points", Metrika, 46, 71-82.
  • Dette, H. (1997c), "E-optimal designs for regression models with quantitative factors - a reasonable choice?", Canadian Journal of Statistics, 25, 531-543.
  • Dette, H. und Munk, A. (1997), "Allocation of treatments for Welch's Test in bioequivalence assessment", Biometrics, 53, 1143-1150.
  • Dette, H. und Neugebauer, H.M. (1997), "Bayesian D-optimal designs for exponential regression models", Journal of Statistical Planning and Inference, 60, 331-345.
  • Dette, H. und Röder, I. (1997), "Optimal discrimination designs for multi-factor experiments", Annals of Statistics, 25, 1161-1175.
  • Dette, H. und Sahm, M. (1997), "Standardized optimal designs for Binary response experiments", South African Statistical Journal, 31, 271-298.
  • Dette, H. und Studden, W.J. (1997), The Theory of Canonical Moments with Applications in Statistics, Probability and Analysis, Wiley, N.Y.
  • Kunert, J. und Sailer, O. (2006), “On Nearly Balanced Designs for Sensory Trials“, Food Quality and Preference, 17, 219-227.
  • Kunert, J. und Sailer, O. (2005), “Randomization of neighbour balanced generalized Youden designs", erscheint in: Journal of Statistical Planning and Inference.
  • Kunert, J. und Stufken, J. (2005), "Optimal crossover designs for two treatments in the presence of mixed and self carryover effects", eingereicht (Journal of the American Statistical Association).
  • Kunert, J., Martin, R.J. und Pooladsaz, S. (2003), “Optimal designs under two related models for interference“, Metrika, 57, 137-143.
  • Kunert, J. (2002), “Statistical Methods to Examine Differences in the Rating of Soft-Drinks Among Different Groups of Consumers”, Food Quality and Preference, 13, 555-559.
  • Kunert, J. und Stufken, J. (2002), “Optimal crossover designs in a model with self and mixed carryover effects”, Journal of the American Statistical Association, 97, 898-906.
  • Kunert, J. (2001a), " Interference designs with circular structure", in: J. Kunert, G. Trenkler (eds.) Mathematical Statistics with Applications in Biometry, Josef Eul, Lohmar (2001), 355-368.
  • Kunert, J. (2001b), "On Repeated Difference Testing", Food Quality and Preference, 12, 358 - 391.
  • Kunert, J., Montag, A. und Pöhlmann, S. (2001), "The Quincunx: History and Mathematics", Statistical Papers, 42, 143 - 169.
  • Kunert, J. und Trenkler, G. (2001), "Mathematical Statistics with Applications in Biometry. Festschrift in Honour of Siegfried Schach", Josef Eul, Lohmar
  • Kunert, J. (2000a), "Randomisation for neighbour-balanced designs", Biometrical Journal, 42, 263-278.
  • Kunert, J. (2000b), "Workshop on the statistical analysis of sensory profiling data: Randomization / permutation / ANOVA", Food Quality and Preference, 11, 141 - 143.
  • Kunert, J. und Martin, R.J. (2000a), "Optimality of type I orthogonal arrays for cross-over models", Journal of Statistical Planning and Inference, 87, 119-124.
  • Kunert, J. und Martin, R. J. (2000b), "On the Determination of Optimal Designs for an Interference Model", Annals of Statistics, 28, 1728 - 1742.
  • Kunert, J. und Meyners, M. (1999), "On the Triangle Test with Replications", Food Quality and Preference, 10, 477-482.
  • Kunert, J. (1998a), "On the analysis of circular balanced crossover designs", Journal of Statistical Planning and Inference, 69, 359-370.
  • Kunert, J. (1998b), "Sensory Experiments as Crossover Studies", Food Quality and Preference, 9, 243-253.
  • Marin-Galiano, M. und Kunert, J. (2006): "Comparison of ANOVA with the Tobit-model for analysing sensory data", Food Quality and Preference, 17, 209-218.
  • Meyners, M. (2001), "Permutation test: Are there Differences in Product Liking?", Food Quality and Preference, 12, 345 - 351.
  • Meyners, M., Kunert, J. und Qannari, E. M. (2000), "Comparing generalized procrustes analysis and STATIS", Food Quality and Preference, 11, 77 - 83.
  • O’Brien, T.E. und Dette, H. (2004), “Efficient experimental design for the Behrens-Fisher problem with application to bioassay”, The American Statistician, 58(2), 138-143.
  • Sailer, O. (2005), "crossdes- A package for Design and Randomization in Crossover Studies", R News, 5, 24-27.
  • Voss, B., Kunert, J., Dahms, S. und Weiss, H. (2000), "A Multinomial Model for the Quality Control of Colony Counting Procedures", Biometrical Journal, 42, 263 - 278.
  • Wameling, A., Kunert, J., Siethmann, B., Blaszkiewicz, M., Van Thriel, C., Zupanic, M. und Seeber, A. (2000), "Individual Toluene Exposure in Rotogravure Printing: Increasing Accuracy of Estimation by Linear Models Based on Protocols of Daily Activities and Other Measures", Biometrics, 56, 1218 - 1221.