LIST OF PUBLICATIONS. 1. J.-P. Kreiss and E. Paparoditis, Bootstrap for Time Series: Theory and Applications, Springer-Verlag, New York, To appear.
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1 LIST OF PUBLICATIONS BOOKS 1. J.-P. Kreiss and E. Paparoditis, Bootstrap for Time Series: Theory and Applications, Springer-Verlag, New York, To appear. JOURNAL PAPERS 61. D. Pilavakis, E. Paparoditis and T. Sapatinas (2019) Testing Equality of Autocovariance Operators for Functional Time Series, submitted. 60. J. Krampe, J.-P. Kreiss and E. Paparoditis (2018) Bootstrap Based Inference for Sparse High- Dimensional Time Series Models, submitted. 59. M. Meyer, E. Paparoditis and J. P. Kreiss (2018) Extending the Validity of Frequency Domain Bootstrap Methods to General Stationary Processes, submitted. 58. A. Leucht, E. Paparoditis and T. Sapatinas (2018) Testing Equality of Spectral Density Operators for Functional Linear Processes, submitted. 57. D. Pilavakis, E. Paparoditis and T. Sapatinas (2017) Moving Block and Tapered Block Bootstrap for Functional Time Series with an Application to the K-Sample Mean Problem, Bernoulli, to appear. 56. E. Paparoditis (2018) Sieve Bootstrap for Functional Time Series, Annals of Statistics, 46, J. Krampe, J. P. Kreiss and E. Paparoditis (2018) Estimated Wold Representation and Spectral Density Driven Bootstrap for Time Series, Journal of the Royal Statistical Society, Series B, 80, M. Fragkeskou and E. Paparoditis (2018) Extending the Range of Validity of the Autoregressive (Sieve) Bootstrap, Journal of Time Series Analysis, Special Issue in Honor of Emanuel Parzen, 39, E. Paparoditis and D. N. Politis (2018) The Asymptotic Size and Power of the Augmented Dickey-Fuller Test for a Unit Root, Econometric Reviews, 37, T. Niebuhr, J. P. Kreiss and E. Paparoditis (2017) Some Properties of the Autoregressive-Aided Block Bootstrap, Electronic Journal of Statistics, 11, E. Paparoditis and T. Sapatinas Bootstrap Based Testing for Functional Data, 2016, Biometrika, 103, E. Paparoditis and P. Preuss, Local Power Properties of Frequency Domain Based Tests for Stationarity, 2016, Scandinavian Journal of Statistics, 43, M. Fragkeskou and E. Paparoditis Inference for the Fourth Order Innovation Cumulant in Linear Time Series, 2016, Journal of Time Series Analysis, 37,
2 48. E. Paparoditis and D. N. Politis, On the Behavior of Nonparametric Density and Spectral Density Estimators at Zero Points of their Support, 2016, Journal of Time Series Analysis, 37, A. Dudek, E. Paparoditis and D. N. Politis Generalized Seasonal Tapered Block Bootstrap, 2016, Statistics and Probability Letters 115, C. Jentsch, E. Paparoditis and D. N. Politis, Block Bootstrap Theory for Multivariate Integrated and Co-Integrated Processes, 2015, Journal of Time Series Analysis, 36, C. Parker, E. Paparoditis and D. N. Politis, Tapered Block Bootstrap for Unit Root Testing, 2015, Journal of Time Series Econometrics, 7, J. Krampe, J. P. Kreiss and E. Paparoditis Hybrid Wild Bootstrap for Nonparametric Trend Estimation in Locally Stationary Time Series, 2015, Statistics and Probability Letters, vol. 101, J.-P. Kreiss and E. Paparoditis, Bootstrapping Locally Stationary Processes, 2015, Journal of the Royal Statistical Society, Series B, vol. 77, E. Paparoditis and P. Preuss Estimation of the Bispectrum of a Locally Stationary Process, 2014, Statistics and Probability Letters, vol. 89, E. Paparoditis and T. Sapatinas Short Term Load Forecasting: The Similar Shape Functional Time Series Predictor, 2013, IEEE Transactions on Power Systems, vol. 28, Issue 4, A. Dudek, J. Leskow, E. Paparoditis and D. N. Politis, A generalized block bootstrap for seasonal time series, Journal of Time Series Analysis, 2012, vol. 35, A. Dowla, E. Paparoditis and D. N. Politis, Local block bootstrap inference for trending time series, 2012, Metrika, J.-P. Kreiss and E. Paparoditis, The Hybrid Wild Bootstrap for Time Series, 2012, Journal of the American Statistical Association, vol. 107, E. Paparoditis and D. N. Politis, Nonlinear Spectral Density Estimation: thresholding the correlogram, 2012, Journal of Time Series Analysis, vol. 33, J.-P. Kreiss and E. Paparoditis, Bootstrap for Dependent Data: A Review (with Discussion and a rejoinder), 2011, Journal of the Korean Statistical Society, vol. 40, and J.-P. Kreiss, E. Paparoditis and D. N. Politis, On the Range of Validity of the Autoregressive Sieve Bootstrap, 2010, Annals of Statistics, vol. 39, A. Berg, E. Paparoditis and D. N. Politis, A Bootstrap Test for Time Series Linearity, 2010, Journal of Statistical Planning and Inference, vol. 140, E. Paparoditis, Validating stationarity assumptions in time series analysis by rolling local periodograms, 2010, Journal of the American Statistical Association, vol. 105, E. Paparoditis, Testing temporal constancy of the spectral structure of a time series, 2009, Bernoulli, vol. 15,
3 31. M. Sergides and E. Paparoditis, Frequency domain tests of semiparametric hypotheses for locally stationary processes, 2009, Scandinavian Journal of Statistics, vol. 36, H. Dette and E. Paparoditis, Bootstrapping frequency domain tests in multivariate time series with an application to testing equality of spectral densities, 2009, Journal of the Royal Statistical Society, Series B, vol 71, A. Antoniadis, E. Paparoditis and T. Sapatinas, Bandwidth selection for functional time series prediction, Statistics and Probability Letters, vol 79, 2009, M. H. Neumann and E. Paparoditis, Simultaneous Confidence Bands in Spectral Density Estimation, Biometrika, vol 95, 2008, M. Sergides and E. Paparoditis, Bootstrapping the Local Periodogram of Locally Stationary Processes, Journal of Time Series Analysis, vol 29, 2008, Corrigendum: Journal of Time Series Analysis, vol 30, M. H. Neumann and E. Paparoditis, Goodness-of-Fit Tests for Markovian Time Series Models, Bernoulli, vol 14, 2008, A. Antoniadis, E. Paparoditis and T. Sapatinas, A Functional Wavelet-Kernel Approach for Continuous- Time Prediction, Journal of the Royal Statistical Society, Series B, vol. 68, 2006, C. Parker, E. Paparoditis and D. N. Politis, Unit Root Testing via the Stationary Bootstrap, Journal of Econometrics, vol. 133, 2006, pp E. Paparoditis and D. N. Politis, Bootstrap Hypothesis Testing in Regression Models, Statistics and Probability Letters, vol. 74, 2005, pp E. Paparoditis, Testing the Fit of a Vector Autoregressive Moving Average Model, Journal of Time Series Analysis, vol. 26, 2005, pp E. Paparoditis and D. N. Politis, Bootstrapping Unit Root Tests for Autoregressive Time Series, Journal of the American Statistical Association, vol. 100, 2005, pp J.-P. Kreiss and E. Paparoditis, Autoregressive Aided Periodogram Bootstrap for Time Series, The Annals of Statistics, vol. 31, 2003, pp E. Paparoditis and D. N. Politis, Residual-Based Block Bootstrap for Unit Root Testing, Econometrica, vol. 71, 2003, pp E. Paparoditis and D. N. Politis, The Local Block Bootstrap, C. R. Acad. Sci. Paris, Series I, vol. 335, 2003, pp E. Paparoditis and D. N. Politis, The Local Bootstrap for Markov Processes, Journal of Statistical Planning and Inference, vol. 108, No 1-2, 2002, pp E. Paparoditis and D. N. Politis, The Tapered Block Bootstrap for General Statistics from Stationary Sequences, The Econometrics Journal, vol. 5, 2002, pp
4 15. E. Paparoditis and D. N. Politis, Tapered Block Bootstrap, Biometrika, vol. 88, 2001, E. Paparoditis and D. N. Politis, A Markovian Local Resampling Scheme for Nonparametric Estimators in Time Series Analysis, Econometric Theory, vol. 17, 2001, pp E. Paparoditis and D. N. Politis, Large-Sample Inference in the General AR(1) Model, Test, vol. 9, 2000, pp M. H. Neumann and E. Paparoditis, On Bootstrapping L 2 -Type Statistics in Density Testing, Statistics and Probability Letters, vol. 50, 2000, pp E. Paparoditis, Spectral Density Based Goodness-of-Fit Tests for Time Series Models, Scandinavian Journal of Statistics, vol. 27, 2000, pp E. Paparoditis and D. N. Politis, The Local Bootstrap for Kernel Estimators under General Dependence Conditions, Annals of the Institute of Statistical Mathematics, vol. 52, 2000, pp E. Paparoditis and D. N. Politis, The Local Bootstrap for Periodogram Statistics, Journal of Time Series Analysis, vol. 20, 1999, pp D.N. Politis, E. Paparoditis and J.P. Romano, Large sample Inference for Irregularly Spaced Dependent Observations Based on Subsampling, Sankhyā, Series A, vol. 60, 1998, pp E. Paparoditis, A Frequency Domain Bootstrap Based Method for Checking the Fit of a Transfer Function Model, Journal of the American Statistical Association, vol. 91, 1996, pp E. Paparoditis, Bootstrapping Autoregressive and Moving Average Parameter Estimates of Infinite Order Vector Autoregressive Processes, Journal of Multivariate Analysis, vol. 57, 1996, pp E. Paparoditis, Bootstrapping Periodogram and Cross Periodogram Statistics of Vector Autoregressive Moving Average Models, Statistics and Probability Letters, Vol. 27, 1996, pp (Erratum, Statistics and Probability Letters, Vol. 31, 1997, p. 243 and Addentum, Statistics and Probability Letters, Vol. 37, 1998, p. 109). 4. E. Paparoditis, On Vector Autocorrelations and Generalized Second Order Functions for Time Series, Journal of Time Series Analysis, vol. 15, 1994, pp E. Paparoditis, A Comparison of Some Autocovariance Based Methods of Autorogressive Moving Average Model Selection, Journal of Statistical Computation and Simulation, vol. 45, 1993, pp E. Paparoditis, Modelling Long Term Dependence in Measurement Errors of Plutonium Concentration, Statistical Papers vol. 33, 1992, pp E. Paparoditis, B. Streitberg Order Identification Statistics in Stationary Autoregressive Moving Average Models: Vector Autocorrelations and the Bootstrap, Journal of Time Series Analysis, vol. 13, 1991, pp BOOK CONTRIBUTIONS 4
5 7. E. Paparoditis Nonparametric Functional Time Series Prediction, in Recent Advances in Functional Data Analysis and Related Topics, Edited by F. Ferraty, 2011, Physica-Verlag: Berlin, pp E. Paparoditis and D. N. Politis, Resampling and Subsampling for Financial Time Series, in Handbook of Financial Time Series, Edited by T. G. Andersen, R. A. Davis, J.-P. Kreiss and T. Mikosch, 2009, Springer-Verlag: New York, pp A. Dowla, E. Paparoditis and D. N. Politis, Locally Stationary Processes and the Local Bootstrap, in Recent Advances and Trends in Nonparametric Statistics, Edited by M. G. Akritas and D. N. Politis, 2003, Elsevier: Amsterdam, pp E. Paparoditis, Frequency Domain Bootstrap for Time Series, in Empirical Process Techniques for Dependent Data, Edited by H. Dehling, T. Mikosch and M. Sørensen, Birkhäuser: Boston, 2002, pp E. Paparoditis and D. N. Politis, The Continuous-Path Block-Bootstrap, in Asymptotics in Statistics and Probability, Edited by Madan L. Puri, 2001, VSP International Science Publishers, pp E. Paparoditis, On Some Power Properties of Goodness-of-Fit Tests in Time Series Analysis, in Recent Advances in Probability and Statistics Edited by Ch. A. Charalambides, N. Balakrishnan and M. V. Koutras 2001, Chapman & Hall, pp D. N. Politis, E. Paparoditis and J. P. Romano, Resampling Marked Point Processes, in Multivariate Analysis, Design of Experiments and Survey Sampling, Edited by S. Ghosh, 1999, Marcell Dekker, Inc., pp REFEREED CONFERENCE PROCEEDINGS 3. E. Paparoditis and H. L. Shang A Sieve Bootstrap Method that Incorporates Model Uncertainty for Constructing Prediction Intervals for Functional Time Series, in ISNPS 2018 Conference Proceedings, Lecture Notes, Springer-Verlag, 2019, To appear. 2. E. Paparoditis and D. N. Politis The Backward Local Bootstrap for Conditional predictive Inference in Nonlinear Time Series, in 4th Hellenic-European Conference on Computer Mathematics and its Applications (HERCMA 98), E. A. Lipitakis (Ed.), Lea Publishing, Athens, Greece, 1998, pp E. Paparoditis, Bootstrapping Some Statistics Useful in Identifying ARMA Models, in Bootstrapping and Related Techniques, (K.-H. Jöckel, G. Rothe and W. Sendler, eds.), 1992, Lecture Notes in Economics and Mathematical Systems, No. 376, Springer-Verlag: Berlin, pp RESEARCH MONOGRAPHS 1. E. Paparoditis, Vector Autocorrelations of Stochastic Processes and the Identification of Autoregressive Moving Average Models, 1990, (in German). Physica-Verlag: Heidelberg. BOOK REVIEWS 5
6 1. Resampling Methods for Dependent Data by S. N. Lahiri. Sankhyā, Series A, To appear. 2. Wavelet Methods in Statistics with R by G. P. Nason. Journal of the Royal Statistical Society, 2010, vol. 173, p
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