Publications

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List of my presentations is here.

List of publications

• Polunchenko, A. S., Pepelyshev, A. (2018). Analytic moment and Laplace transform formulae for the quasi-stationary distribution of the Shiryaev diffusion on an interval. Stat. papers.
• Dette H., Pepelyshev A., Zhigljavsky A. (2018). The BLUE in continuous-time regression models with correlated errors. Annals of Statistics.
• Pepelyshev, A., Zhigljavsky, A., Zilinskas, A. (2018). Performance of global random search algorithms for large dimensions. Journal of Global Optimization, 71, 57-71.
• Pepelyshev, A., Zhigljavsky, A., Kornikov, V. (2017). Statistical estimation in global random search algorithms in case of large dimensions. Lecture Notes in Computer Science, 10556, 364-369.
• Pepelyshev, A., Polunchenko, A. S. (2017). Real-time financial surveillance via quickest change-point detection methods. Statistics and Its Interface, 10, 93-106.
• Pepelyshev, A., Zhigljavsky, A. (2017). SSA analysis and forecasting of records for Earth temperature and ice extents. Statistics and Its Interface, 10, 151-163.
• Pepelyshev, A., Staroselskiy, Y., Zhigljavsky, A., Guchenko, R. (2016). Adaptive Targeting in Online Advertisement: Models Based on Relative Influence of Factors. In Machine Learning, Optimization, and Big Data. Springer International Publishing.
• Pepelyshev, A., Sovetkin, E., Steland, A. (2016). Panel-based stratified cluster sampling and analysis for photovoltaic outdoor measurements. Applied stochastic models in business and industry.
• Borodich, F. M., Pepelyshev, A., Savencu, O. (2016). Statistical approaches to description of rough engineering surfaces at nano and microscales. Tribology International, 103, 197-207.
• Dette, H., Pepelyshev, A., Zhigljavsky, A. (2016). Optimal designs for regression models with autoregressive errors. Statistics & Probability Letters, 116, 107-115.
• Pepelyshev, A., Staroselskiy, Y. and Zhigljavsky, A. A. (2016). Adaptive designs for optimizing online advertisement campaigns. mODa 11 - Advances in Model-Oriented Design and Analysis. Contributions to statistics. Springer Verlag.
• Dette, H., Pepelyshev, A., Zhigljavsky, A. (2016). Optimal designs in regression with correlated errors. Annals of Statistics, 44, 113-152.
• Pepelyshev, A., Staroselskiy, Y., Zhigljavsky, A. (2015). Adaptive Targeting for Online Advertisement. In Machine Learning, Optimization, and Big Data. Springer International Publishing. 240-251.
• Borodich, F. M., Pepelyshev, A. and Savencu, O. (2015). Micro and nano scale statistical properties of rough surfaces of significance in their friction. Procedings of the 6th Vienna International Conference NANO-TECHNOLOGY - VIENNANO '15, Wiener Neustadt, Austria, 23-25 November 2015.
• Dette, H., Pepelyshev, A., Zhigljavsky, A. (2015). Design for linear regression models with correlated errors. Handbook of Design and Analysis of Experiments, CRC press, 236-276.
• Melas, V. B., Pepelyshev, A., Shpilev, P., Salmaso, L., Corain, L., Arboretti, R. (2015). On the optimal choice of the number of empirical Fourier coefficients for comparison of regression curves. Statistical Papers, 56(4), 981-997.
• Corain, L., Melas, V. B., Pepelyshev, A., Salmaso, L. (2014). New insights on permutation approach for hypothesis testing on functional data. Advances in Data Analysis and Classification, 8, 339-356.
• Dette H., Pepelyshev A., Zhigljavsky A. (2014). Nearly universally optimal designs for models with correlated observations. Computational Statistics & Data Analysis, 71(C), 1103-1112.
• Pepelyshev A., Rafajlowicz E., Steland A. (2014). Estimation of the quantile function using Bernstein-Durrmeyer polynomials. Journal of Nonparametric Statistics 26, 1-20.
• Avellan-Hampe A., Pepelyshev A., Steland A. (2014). Acceptance sampling plans for photovoltaic modules with two-sided specification limits. Progress in photovoltaics, 22, 603-611.
• Dette H., Pepelyshev A., Zhigljavsky A. (2013). Optimal design for linear models with correlated observations. Annals of Statistics, 41, 143-176.
• Pepelyshev A. (2013). Optimal design for multivariate models with correlated observations. MODA 10---Advances in model-oriented design and analysis, Contrib. Statist. 203-210.
• Wang H., Pepelyshev A., Flournoy N. (2013). Optimal design for the bounded log-linear regression model. MODA 10---Advances in model-oriented design and analysis, Contrib. Statist. 237-245.
• Golyandina N., Pepelyshev A., Steland A. (2012). New approaches to nonparametric density estimation and selection of smoothing parameters. Computational Statistics and Data Analysis, 56(7), 2206-2218.
• Meisen S., Pepelyshev A., Steland A. (2012). Quality assessment in the presence of additional data. Frontiers in Statistical Quality Control, Vol. 10, 251-274.
• Dette H., Pepelyshev A., Wong W.K. (2012). Optimal designs for composed models in pharmacokinetic-pharmacodynamic experiments. Journal of Pharmacokinetics and Pharmacodynamics, 39, 295-311.
• Dette H., Pepelyshev A., Wong W.K. (2011). Optimal experimental design strategies for detecting hormesis. Risk Analysis, 31, 1949-1960.
• Dette H., Holland-Letz T., Pepelyshev A. (2011). A geometric characterization of optimal designs for regression models with correlated observations. JRSS B, 73, 239-252.
• Pepelyshev A. (2011) Fixed-domain asymptotics of the maximum likelihood estimator and the Gaussian process approach for deterministic models. Statistical Methodology, 8, 356-362.
• Dette H., Melas V.B., Pepelyshev A. (2011). Optimal design for smoothing splines. Ann. Inst. Statist. Math. 63(5) 981-1003.
• Zhigljavsky A., Dette H., Pepelyshev A. (2010). A new approach to optimal design for linear models with correlated observations. J. Amer. Stat. Ass. 105, 1093-1103.
• Dette H., Pepelyshev A. (2010) Generalized Latin hypercube design for computer experiments. Technometrics 52, 421-429.
• Pepelyshev A. (2010) The role of the nugget term in the Gaussian process method. MODA 9---Advances in model-oriented design and analysis, Contrib. Statist. 149-156.
• Pepelyshev A., Zhigljavsky A. (2010). Assessing the stability of long-horizon SSA forecasting. Statistics and Its Interface 3, 321-327.
• Dette H., Pepelyshev A. (2010). NPUA: A new approach for the analysis of computer experiments. Chemometrics and Intelligent Laboratory Systems 104, 333-340.
• Dette H., Pepelyshev A., T. Holland-Letz (2010). Optimal designs for random effect models with correlated errors with applications in population pharmacokinetics. Annals of Appl. Stat. 4, 1430-1450. journalarxiv
• Dette H., Melas V.B., Pepelyshev A. (2010). Optimal designs for estimating the slope of a regression. Statistics 44, 617 - 628.
• Corain L., Panozzo G., Pepelyshev A., Rossi S., Salmaso L. (2010). Estimating and Testing for Influence of Specific Structural Factors on Aging of Refrigerated Vehicles, Pub. Inst. Stat. Univ. Paris, LIV, 3, 25-40.
• Dette H., Pepelyshev A., Shpilev P., Wong W.K. (2010). Optimal designs for discriminating between dose response models in toxicology studies. Bernoulli 16, 1164-1176.
• Pepelyshev A. (2009). Improvement of random LHD for high dimensions. Proceedings of the 6th St. Petersburg Workshop on Simulation, 1091-1096.
• Pepelyshev A., Poli I., Melas V.B. (2009). Uniform coverage designs for mixture experiments. J. Statist. Plann. Inf. 139, 3442-3452.
• Dette H., Leonenko N., Pepelyshev A., Zhigljavsky A. (2009). Asymptotic optimal designs under long-range dependence error structure. Bernoulli 15, 1036-1056.
• Dette H., Pepelyshev A., Shpilev P., Wong W.K. (2009). Optimal designs for estimating critical effective dose under model uncertainty in a dose response study. Statistics and Its Interface, 2, 27-36.
• Dette H., Pepelyshev A., Wong W.K. (2009). Optimal designs for dose-finding experiments in toxicity studies. Bernoulli, 15, 124-145.
• Dette H., Pepelyshev A., Zhigljavsky A. (2008). Improving updating rules in multiplicative algorithms for computing D-optimal designs. Com. Stat. and Data Analysis. 53, 312-320.
• Dette H., Melas V.B., Pepelyshev A. (2008). Optimal designs for free knot least squares splines. Statist. Sinica 18, 1047-1062.
• Dette H., Pepelyshev A. (2008). Efficient experimental designs for sigmoidal growth models. J. Statist. Plann. Inf. 138, 2-17.
• Dette H., Bretz F., Pepelyshev A., Pinheiro J. (2008). Optimal designs for dose-finding studies. J. Amer. Statist. Assoc. 103, no. 483, 1225-1237.
• Dette H., Kunert J., Pepelyshev A. (2008). Exact optimal designs for weighted least squares analysis with correlated errors. Statistica Sinica, 18, 135-154.
• Arboretti G.R., Corain L., Franceschini S., Pepelyshev A., Rossi S. (2008). Permutation Testing for Alternative Nonlinear Models with Application to Aging Curves of Refrigerated Vehicles, Proceedings in Computational Statistics (Edited by Paula Brito), International Conference on Computational Statistics, Porto - Portugal, August 24th-29th 2008, 659-667.
• Biedermann S., Dette H., Pepelyshev A. (2007). Optimal discrimination designs for exponential regression models. J. Statist. Plann. Inference 137, no. 8, 2579--2592.
• Melas V.B., Pepelyshev A. (2007). On representing maximin efficient designs by Taylor series. J. Statist. Plann. Inference 137, no. 8, 2689-2702.
• Pepelyshev A. (2007). Optimal designs for the exponential model with correlated observations. mODa 8---Advances in model-oriented design and analysis, 165-172, Contrib. Statist.
• Dette H., Melas V.B., Pepelyshev A. (2007). Optimal designs for statistical analysis with Zernike polynomials. Statistics 41, no. 6, 453-470.
• S. Biedermann, Dette H., Pepelyshev A. (2006). Some robust design strategies for percentile estimation in binary response models. Canad. J. Stat. 34, no. 4, 603-622.
• Dette H., Melas V.B., Pepelyshev A. (2006). Local c- and E-optimal designs for exponential regression models. Ann. Inst. Statist. Math. 58, no. 2, 407-426.
• Dette H., Lopez I. M., Ortiz-Rodriguez I. M., Pepelyshev A. (2006). Maximin efficient design of experiment for exponential regression models. J. Statist. Plann. Inference 136, no. 12, 4397--4418.
• Dette H., Melas V.B., Pepelyshev A. (2005). Optimal designs for 3D shape analysis with spherical harmonic descriptors. Annals of Statistics, Vol. 33, No. 6, 2758-2788
• Dette H., Melas V.B., Pepelyshev A., N. Strigul (2005). Design of experiments for the Monod model - robust and efficient designs. J. of Theor. Biology. 234, 537-550.
• Melas V.B., Pepelyshev A. (2005). On the study of maximin efficient designs by the functional approach. Proceedings of the 5th St. Petersburg Workshop on Simulation / ed. by Ermakov et al., 479-484.
• Dette H., Melas V.B., Pepelyshev A. (2004). Optimal designs for estimating individual coefficients in polynomial regression - a functional approach. J. of Statis. Plan. and Inference, 118, 201-219.
• Dette H., Melas V.B., Pepelyshev A. (2004). Optimal designs for a class of nonlinear regression models. Annals of Statistics. V 32, N 5, 2004, 2142-2167.
• Biedermann S., Dette H., Pepelyshev A. (2004). Maximin optimal designs for a compartmental model. mODa 7---Advances in model-oriented design and analysis, 41--49, Contrib. Statist., Physica, Heidelberg, 2004.
• Dette H., Melas V.B., Pepelyshev A. (2003). Standardized maximin E-optimal designs for Michaelis-Menten model. Statistica Sinica, 13, 1147-1163.
• Melas V.B., Pepelyshev A., Cheng R.C.H. (2003). Designs for estimating an extremal point of quadratic regression models in a hyperball. Metrika, 58. 193--208.
• Dette H., Melas V.B., Pepelyshev A., Strigul N. (2003). Efficient design of experiment in the Monod model. J. Roy. Statist. Soc., Ser. B, 65, 725-742.
• Dette H., Melas V.B., Pepelyshev A. (2002). D-optimal designs for trigonometric regression models on a partial circle. Annals of the Institute of Statistical Mathematics, vol. 54, N 4, 945-959.
• Cheng R.C.H., Melas V.B., Pepelyshev A. (2000). Optimal design for evaluation of an extremum point. Optimum Design 2000. Eds. A.Atkinson, B.Bogacka, A.Zhigljavsky. Kluwer, 15-24.

Edited volumes

• Ermakov S.M., Melas V.B., Pepelyshev A. eds. (2009). Proceedings of the 6th St. Petersburg Workshop on Simulation.
• Ermakov S.M., Melas V.B., Pepelyshev A. eds. (2005). Proceedings of the 5th St. Petersburg Workshop on Simulation.