Papers in journals

  • L. Horvath, P. Kokoszka, and S.Lu, Variable Selection Based Testing for Parameter Changes in Regression with Autoregressive Dependence, Journal of Business & Economic Statistics 00, 000-000, 2024 pdf file
  • C. Baek, P. Kokoszka, and X. Meng, Test of change point versus long-range dependence in functional time series, Journal of Time Series Analysis, 00, 000-000, 2023 pdf file, Supporting information, Code
  • P. Kokoszka, T. Kutta, D. Singh and H. Wang, Limit theorems for a higher order time dependent Markov chain model, Probability and Mathematical Statistics, 43, 121-139, 2023 pdf file
  • M. Kim and P. Kokoszka, Asymptotic and finite sample properties of Hill-type estimators in the presence of errors in observations, Journal of Nonparametric Statistics, 5, 1-18, 2023 pdf file
  • M. Kim, P. Kokoszka and G.Rice, White noise testing for functional time series, Statistical Surveys, 17, 119-168, 2023 pdf file
  • Rimkus, M., Kokoszka, P, Prabakar, K. and Wang H., Toward statistical real-time power fault detection, Communications in Statistics-Case Studies, Data Analysis and Applications 9, 1196--1217, 2023
  • P. Kokoszka, M. Rimkus, S. Hosur, D. Duan and H. Wang, Detection and localization of faults in a regional power grid, Austrian Journal of Statistics, 52, 143-162, 2023 pdf file
  • P. Kokoszka and R. Kulik, Principal component analysis of infinite variance functional data Journal of Multivariate Analysis, 193, 105123, 2023 pdf file
  • F. Sabzikar and P. Kokoszka, Tempered functional time series, Journal of Time Series Analysis, 44, 280-293, 2023 pdf file
  • M. Krzysko, L. Smaga and P. Kokoszka, Marginal distance and Hilbert-Schmidt covariances-based independence tests for multivariate functional data, Journal of Artificial Intelligence Research, 73, 1355-1384, 2022 pdf file
  • P. Kokoszka, D. Singh and H. Wang, Long term behavior of incomplete and time varying product ratings, Statistics and Probability Letters, 184, 109387, 2022 pdf file
  • M. Kim and P. Kokoszka, Extremal dependence measure for functional data, Journal of Multivariate Analysis, 189, 104887, 2022 pdf file
  • L. Horváth, P. Kokoszka, J. Vanderdoes and S. Wang, Inference in functional factor models with applications to yield curves, Journal of Time Series Analysis, 43 , 872–894, 2022 pdf file
  • T. Kuenzer, S. Hörmann and P. Kokoszka, Testing normality of spatially indexed functional data, Canadian Journal of Statistics, 50 , 304–326, 2022, pdf file .
  • A. Petersen, C. Zhang and P. Kokoszka, Modeling probability density functions as data objects, Econometrics and Statistics, 21 , 159–178, 2022 pdf file
  • C. Zhang, P. Kokoszka and A. Petersen, Wasserstein autoregressive models for density time series, Journal of Time Series Analysis, 43 , 30–52, 2022 pdf file , Supporting information
  • J. Nicholson, P. Kokoszka, R. Lund, P. Kiessler and J. Sharp, Renewal model for anomalous traffic in Internet2 links, Statistical Modelling, 22(5), 430-456, 2022 pdf file
  • L. Horváth, P. Kokoszka and S. Wang, Monitoring for a change point in a sequence of distributions, Annals of Statistics, 49, 2271-2291, 2021 pdf file , Supplementary Material
  • T. Kuenzer, S. Hörmann and P. Kokoszka, Principal component analysis of spatially indexed functions, Journal of American Statistical Association, 116 , 1444–1456, 2021, pdf file .
  • S. Butler, P. Kokoszka, H. Miao and HL Shang, Neural network prediction of crude oil futures using B-splines, Energy Economics, 94, 2021, pdf file
  • J. French and P. Kokoszka, A sandwich smoother for spatio--temporal data, Spatial Statistics, 42 , 0000–0000, 2021 pdf file , Archived data/code, hero R package.
  • L. Horvath, P. Kokoszka, and S. Wang, Testing normality of data on a multivariate grid, Journal of Multivariate Analysis, 179, 0000–0000, 2020 pdf file , Supplement
  • P-S. Zhong, J. Li and P. Kokoszka, Multivariate analysis of variance and change points estimation for high-dimensional longitudinal data, Scandinavian Journal of Statistics, 48 , 375–405, 2021
  • T. Gorecki, L. Horvath and P. Kokoszka, Tests of normality of functional data, International Statistical Review, 88, 677-697, 2020 pdf file
  • P. Kokoszka, H. Nguyen, H. Wang and L. Yang, Statistical and probabilistic analysis of interarrival and waiting times of Internet2 anomalies, Statistical Methods & Applications, 29 , 727–744, 2020 pdf file
  • P. Kokoszka and N. Mohammadi Jouzdani, Frequency domain theory for functional time series: Variance decomposition and an invariance principle, Bernoulli, 26 , 2383-2399, 2020 pdf file
  • M. Kim and P. Kokoszka, Consistency of the Hill estimator for time series observed with measurement errors, Journal of Time Series Analysis, 41 , 421-453, 2020 pdf file
  • P. Kokoszka, S. Stoev and Q. Xiong, Principal components analysis of regularly varying functions, Bernoulli, 25,3864–3882 , 2019 pdf file
  • P. Kokoszka, H. Miao, A. Petersen, and HL. Shang, Forecasting of density functions with an application to cross--sectional and intraday returns, International Journal of Forecasting, 25, 1304--1317, 2019 pdf file
  • M. Kim and P. Kokoszka, Hill estimator of projections of functional data on principal components, Statistics, 53 , 699-720, 2019 pdf file
  • J. French, P. Kokoszka S. Stoev and L. Hall, Quantifying the risk of heat waves using extreme value theory and spatio-temporal functional data, Computational Statistics and Data Analysis, 131, 176-193, 2019 pdf file , Supporting Information
  • S. Hörmann, P. Kokoszka and G. Nisol, Testing for periodicity of functional time series, The Annals of Statistics, 46 , 2960-2984, 2018 pdf file
  • P. Kokoszka and M. Reimherr, Some recent developments in inference for geostatistical functional data, Revista Colombiana de Estadνstica, 42 , 101-122, 2019 pdf file
  • P. Constantinou, P. Kokoszka and M. Reimherr, Testing Separability of Functional Time Series, Journal of Time Series Analysis, 39, 731-747, 2018 pdf file , Supporting Information
  • L. Kidzinski, P. Kokoszka and N. Mohammadi, Principal components analysis of periodically correlated functional time series, Journal of Time Series Analysis, 39, 502-522, 2018 pdf file , Supporting Information
  • T. Gorecki, S. Hörmann, L. Horvath and P. Kokoszka, Testing normality of functional time series, Journal of Time Series Analysis, 39, 471-487, 2018 pdf file , Supporting Information
  • P. Kokoszka, H. Miao, M. Reimherr and B. Taoufik, Dynamic functional regression with application to the cross--section of returns, Journal of Financial Econometrics 16, 461-485, 2018 pdf file
  • T. Gorecki, L. Horvath and P. Kokoszka, Change point detection in heteroscedastic time series, Econometrics and Statistics, 7, 63-88, 2018 pdf file
  • P. Kokoszka and Q. Xiong, Extremes of projections of functional time series on data-driven basis systems, Extremes, 21, 177-204, 2018 pdf file
  • P. Kokoszka, H. Miao, S. Stoev and B. Zheng Risk Analysis of Cumulative Intraday Return Curves, Journal of Time Series Econometrics, 11, 2018 pdf file
  • P. Kokoszka, G. Rice and H. L. Shang, Inference for the autocovariance of a functional time series under conditional heteroscedasticity Journal of Multivariate Analysis, 162 , 32-50, 2017 pdf file
  • P. Constantinou, P. Kokoszka and M. Reimherr, Testing separability of space-time functional processes, Biometrika, 104, 425-437, 2017 pdf file , Supplemental Material
  • O. Gromenko. P. Kokoszka and J. Sojka, Evaluation of the cooling trend in the ionosphere using functional regression with incomplete curves, Annals of Applied Statistics, 11, 898-918, 2017 pdf file
  • P. Kokoszka, H. Miao and B. Zheng, Testing for asymmetry in betas of cumulative returns: Impact of the financial crisis and crude oil price, Statistics and Risk Modeling, 34, 33-54, 2017 pdf file
  • O. Gromenko, P. Kokoszka and M. Reimherr, Detection of change in the spatiotemporal mean function, Journal of the Royal Statistical Society (B), 79, 29-50, 2017 pdf file
  • A. Jach and P. Kokoszka, Wavelet semi-parametric inference for long memory in volatility in the presence of a trend, Journal of Statistical Computation and Simulation, 87, 1498-1519, 2017 pdf file
  • P. Burdejova, W. Hardle, P. Kokoszka and Q. Xiong, Change point and trend analyses of annual expectile curves of tropical storms, Econometrics and Statistics , 1 , 101-117, 2017 pdf file
  • P. Bardsley, L. Horvath, P. Kokoszka and G. Young, Change point tests in functional factor models with application to yield curves, The Econometrics Journal , 20, 86-117, 2017 pdf file
  • P. Kokoszka and G. Young, Testing trend stationarity of functional time series with application to yield and daily price curves, Statistics and Its Interface, 10, 81-92, 2017 pdf file
  • P. Kokoszka and G. Young, KPSS test for functional time series, Statistics , 50, 957-973, 2016 pdf file
  • P. Kokoszka and M. Reimherr and N. Woelfing, A randomness test for functional panels, Journal of Multivariate Analysis , 151, 37-53, 2016 pdf file
  • S. Hörmann, L. Kidzinski and P. Kokoszka, Estimation in functional lagged regression, Journal of Time Series Analysis , 36, 541-561, 2015 pdf file
  • P. Kokoszka, H. Miao and X. Zhang, Functional dynamic factor model for intraday price curves, Journal of Financial Econometrics , 13, 456-477, 2015 pdf file
  • L. Horvath, P. Kokoszka and G. Rice, Testing stationarity of functional time series, Journal of Econometrics , 179, 66-82, 2014 pdf file
  • S. Fremdt, L. Horvath, P. Kokoszka and J. Steinebach, Functional data analysis with increasing number of projections, Journal of Multivariate Analysis , 124, 313-332, 2014 pdf file
  • P. Kokoszka and M. Reimherr, Predictability of shapes of intraday price curves, Econometrics Journal , 16, 285-308, 2013 pdf file
  • P. Kokoszka and M. Reimherr, Asymptotic normality of the principal components of functional time series, Stochastic Processes and their Applications , 123, 1546-1562, 2013 pdf file
  • P. Kokoszka and M. Reimherr, Determining the order of the functional autoregressive process, Journal of Time Series Analysis , 34 , 116-129, 2013 pdf file
  • S. Fremdt, L. Horvath, P. Kokoszka, J. Steinebach, Testing the equality of covariance operators in functional samples, Scandinavian Journal of Statistics , 40, 138-152, 2013 pdf file
  • L. Horvath, P. Kokoszka and R. Reeder, Estimation of the mean of functional time series and a two sample problem, Journal of the Royal Statistical Society (B), 75 , 103-122, 2013 pdf file , code , data
  • S. Hörmann and P. Kokoszka, Consistency of the mean and the principal components of spatially distributed functional data, Bernoulli , 19 , 1535-1558, 2013 pdf file
  • R. Gabrys, S. Hörmann and P. Kokoszka, Monitoring the intraday volatility pattern, Journal of Time Series Econometrics , 5 , 87-116, 2013 pdf file
  • O. Gromenko and P. Kokoszka, Nonparametric inference in small data sets of spatially indexed curves with application to ionospheric trend determination, Computational Statistics and Data Analysis , 59 , 82-94, 2013 pdf file
  • O. Gromenko, P. Kokoszka, L. Zhu, J. Sojka, Estimation and testing for spatially distributed curves with application to ionospheric and magnetic field trends, The Annals of Applied Statistics, 6 , 669-696, 2012 pdf file
  • O. Gromenko and P. Kokoszka, Testing the equality of mean functions of ionospheric critical frequency curves Journal of the Royal Statistical Society (C), 61 , 715-731, 2012 pdf file
  • P. Kokoszka and X. Zhang, Functional prediction of cumulative intraday returns, Statistical Modelling , 12 , 377-398, 2012 pdf file
  • D. Didericksen, P. Kokoszka. and X. Zhang, Empirical properties of forecasts with the functional autoregressive model, Computational Statistics, 27 , 285-298, 2012 pdf file
  • P. Kokoszka, Dependent functional data (spotlight article), ISRN Probability and Statistics , Article ID 958254, 30 pages, 2012 pdf file
  • R. R. Gilles, Q-Y. Chung, S-Y Wang, and P. Kokoszka, Incorporation of Pacific SSTs in a time series model towards a longer-term forecast for the Great Salt Lake elevation, Journal of Hydrometeorology , 12 , 474-80, 2011 pdf file
  • P. Kokoszka and D. Politis, Nonlinearity of ARCH and Stochastic Volatility models and Bartlett's formula, Probability and Mathematical Statistics, 31 , 47-59, 2011 pdf file
  • R. Gabrys, L. Horvath, P. Kokoszka, Tests for error correlation in the functional linear model, Journal of the American Statistical Association, 105 , 1113-1125, 2010 pdf file , Extended Version
  • S. Hörmann and P. Kokoszka, Weakly dependent functional data, The Annals of Statistics, 38 , 1845-1884, 2010 pdf file
  • U. Hassler and P. Kokoszka, Impulse response coefficients of fractionally integrated processes with long memory, Econometric Theory, 26 , 1855–1861, 2010 pdf file
  • I. Maslova, P. Kokoszka, J. Sojka, and L. Zhu, Estimation of Sq variation by means of multiresolution and principal component analyses, Journal of Atmospheric and Solar-Terrestrial Physics , 72 , 625-632, 2010 pdf file
  • A. Jach and P. Kokoszka, Empirical wavelet analysis of tail and memory properties of LARCH and FIGARCH processes, Computational Statistics, 25 , 163-182, 2010 pdf file
  • I. Maslova, P. Kokoszka, J. Sojka, and L. Zhu, Statistical significance testing for the association of magnetometer records at high-, mid- and low latitudes during substorm days, Planetary and Space Science , 58 , 437–445, 2010 pdf file
  • L. Horvath, M. Huskova, P. Kokoszka, Testing the stability of the functional autoregressive process, Journal of Multivariate Analysis , 101, 352-367, 2010 pdf file

  • Z. Xu, L. Zhu, J. Sojka and P. Kokoszka, Wavelet cross--spectrum analysis of the ring current using magnetic records from multiple low--latitude stations Journal of Geophysical Research , 114, A05309, 2009 pdf file
  • L. Horvath, P. Kokoszka and M. Reimherr, Two sample inference in the functional linear model Canadian Journal of Statistics, 37 , 571-591, 2009 pdf file
  • A. Aue, R. Gabrys, L. Horvath, P. Kokoszka, Estimation of a change--point in the mean function of functional data, Journal of Multivariate Analysis, 100 , 2254-2269, 2009 pdf file
  • I. Berkes, R. Gabrys, L. Horvath, P. Kokoszka, Detecting changes in the mean of functional observations, Journal of the Royal Statistical Society , 71, 927-946, 2009 pdf file
  • I. Maslova, P. Kokoszka, J. Sojka, and L. Zhu, Removal of nonconstant daily variation by means of wavelet and functional data analysis, Journal of Geophysical Research , 114, A03202, doi:10.1029/2008JA013685, 2009 pdf file
  • A. Jach and P. Kokoszka, Robust wavelet domain estimation of the fractional difference parameter in heavy--tailed time series: an empirical study, Methodology and Computing in Applied Probability DOI: 10.1007/s11009-008-9105-3, 2008 pdf file
  • A.Jach and P. Kokoszka, Wavelet based confidence intervals for the self-similarity parameter, Journal of Statistical Computation and Simulation, 78, 1179-1198, 2008 pdf file
  • Z. Xu, L. Zhu, J. Sojka, P. Kokoszka, A. Jach, An Assessment Study of the Wavelet-Based Index of Magnetic Storm Activity (WISA) and Its Comparison to the Dst Index, Journal of Atmospheric and Solar-Terrestrial Physics 70, 1579-1588 , 2008 pdf file
  • P. Kokoszka, I. Maslova, J. Sojka, L. Zhu, Testing for lack of dependence in the functional linear model, Canadian Journal of Statistics, Vol. 36, No. 2, 207-222, 2008 pdf file
  • A. Aue, L. Horvath, M. Huskova and P. Kokoszka, Testing for changes in polynomial regression Bernoulli, 14 , 637-660, 2008 pdf file
  • L. Horvath and P. Kokoszka, Sample autocovariances of long memory time series Bernoulli, 14 , 405-418 , 2008 pdf file
  • A. Jach and P. Kokoszka, Wavelet domain test for long-range dependence in the presence of a trend Statistics, 42 , 101-113, 2008 pdf file
  • L. Horvath, P. Kokoszka and R. Zitikis, Distributional analysis of empirical volatility in GARCH processes Journal of Statistical Inference and Planning, 138 , 3578-3589, 2008 pdf file
  • A. Aue, L. Horvath, P. Kokoszka, J. Steinebach, Monitoring shifts in mean: asymptotic normality of stopping times Test, 17 , 515-530, 2008 pdf file
  • P. Kokoszka, J. Krolczyk, and M. Tukiendorf, Adaptacja funkcji geostatystycznej do analizy przestrzennego rozkladu dwuskladnikowej mieszaniny ziarnistej (Adaptation of a geostatistical function to the analysis of the spatial distribution of a two component granular blend), Inzyniernia Rolnicza , 90, 101-107, 2007 pdf file
  • A. Zhang, R. Gabrys and P. Kokoszka, Discriminating between long memory and volatility shifts Austrian Journal of Statistics, 36 , 253-275, 2007 pdf file
  • R. Gabrys and P. Kokoszka, Portmanteau test of independence for functional observations Journal of the American Statistical Association, 102 , 1338-1348, 2007 pdf file
  • R. Bhansali, L. Giraitis and P. Kokoszka, Convergence of quadratic forms with nonvanishing diagonal Statistics and Probability Letters, 77 , 726-734, 2007 pdf file
  • L. Horvath, P. Kokoszka and J. Steinebach, On sequential detection of parameter changes in linear regression, Statistics and Probability Letters, 77 , 885-895, 2007 pdf file
  • R. Bhansali, L. Giraitis and P. Kokoszka, Approximations and limit theory for quadratic forms of linear variables Stochastic Processes and their Applications, 117 , 71-95, 2007 pdf file
  • L. Horvath, P. Kokoszka and R. Zitikis, Sample and implied volatility in GARCH models Journal of Financial Econometrics, doi: 10.1093/jjfinec/nbl002, 2006 pdf file
  • A. Aue, L. Horvath, M. Huskova and P. Kokoszka, Change--point monitoring in linear models with conditionally heteroskedastic errors Econometrics Journal, Vol. 9, 373-403, 2006 pdf file
  • A. Jach, P. Kokoszka, J. Sojka, L. Zhu, Wavelet--based index of magnetic storm activity. Journal of Geophysical Research, 111 , A09215, 2006 pdf file
  • P. Kokoszka, I. Maslova, J. Sojka, L. Zhu, Probability tails of wavelet coefficients of magnetometer records. Journal of Geophysical Research, Vol. 111, No. A6, A06202, 10.1029/2005JA011486, 2006 pdf file
  • R. Bhansali, L. Giraitis and P. Kokoszka, Estimation of the memory parameter by fitting fractionally differenced autoregressive models Journal of Multivaiate Analysis, 97 Issue 10, 2101-2130, 2006 pdf file
  • I. Berkes, L. Horvath, P. Kokoszka, Q. Shao, On discriminating between long-range dependence and changes in mean The Annals of Statistics, 34, 1140-1165, 2006
  • L. Horvath, P. Kokoszka and A. Zhang, Monitoring constancy of variance in conditionally heteroskedastic time series Econometric Theory, 22 , 373-402, 2006
  • L. Horvath, P. Kokoszka and R. Zitikis, Testing for Stochastic dominance using the weighted McFaden statistic Journal of Econometrics, 133 , 191-205, 2006
  • I. Berkes, L. Horvath and P. Kokoszka, Near integrated GARCH sequences, Annals of Applied Probability, 15 , 890-913, 2005
  • I. Berkes, L. Horvath, P. Kokoszka, Q. Shao, Almost sure convergence of the Bartlett estimator Periodica Mathematica Hungarica, 51 , 11-25, 2005 pdf file
  • I. Berkes, L. Horvath and P. Kokoszka, Testing for parameter constancy in GARCH(p,q) models Statistics and Probability Letters, 70 , 263-273, 2004
  • I. Berkes, E. Gombay, L. Horvath and P. Kokoszka, Sequential change-point detection in GARCH(p,q) models, Econometric Theory, 20 , 1140-1167, 2004
  • A. Jach and P. Kokoszka, Subsampling unit root tests for heavy-tailed observations Methodology and Computing in Applied Probability, 6 , 73--97, 2004
  • L. Horvath, M. Huskova, P. Kokoszka and J. Steinebach, Monitoring changes in linear models Journal of Statistical Planning and Inference, 126 , 225-251, 2004
  • L.Horvath, P. Kokoszka and G. Teyssiere, Bootstrap misspecification tests for ARCH based on the empirical process of squared residuals Journal of Statistical Computation and Simulation, 74 , 469-485, 2004
  • P. Kokoszka and M. Wolf, Subsampling the mean of heavy-tailed dependent observations, Journal of Time Series Analysis 25 , 217-234, 2004
  • I. Berkes, L. Horvath and P. Kokoszka, A Weighted Goodness-of-Fit Test for GARCH(1,1) Specification, Lithuanian Mathematical Journal , 44, 1-17, 2004 pdf file
  • L. Giraitis, P. Kokoszka, R. Leipus and G. Teyssiere, On the power of the R/S-type tests against contiguous and semi long memory alternatives Actae Applicandae Mathematicae 78 , 285--299, 2003
  • L. Horvath and P. Kokoszka A bootstrap approximation to a unit root test statistic for heavy-tailed observations Statistics and Probability Letters, 62 , 163-173, 2003
  • I. Berkes, L. Horvath and P. Kokoszka, Asymptotics for GARCH squared residual correlations, Econometric Theory , 19 , 515-540, 2003
  • I. Berkes, L. Horvath and P. Kokoszka, GARCH processes: structure and estimation, Bernoulli 9 , 201-207, 2003
  • I. Berkes, L. Horvath and P. Kokoszka, Estimation of the maximal moment exponent of a GARCH(1,1) sequence, Econometric Theory 19 , 565-586, 2003
  • (with L.Giraitis, R.Leipus and G.Teyssiere ) Rescaled variance and related tests for long memory in volatility and levels, Journal of Econometrics , 112 , 265-294, 2003
  • (with R. Bhansali) Computation of the forecast coefficients for multistep prediction of long-range dependent time series, International Journal of Forecasting , 18 , 181-206, 2002
  • (with L.Horvath) Change-point detection with non-parametric regression, Statistics , 36 , 9-31, 2002 pdf file
  • (with L.Giraitis and R.Leipus) Testing for long memory in the presence of a general trend, Journal of Applied Probability, 38 , 1033--1054, 2001
  • (with R. Bhansali) Prediction of long memory time series: an overview , Estadistica , 53 , 41-96, 2001
  • (with L.Horvath) Large sample distribution of ARCH(p) squared residual correlations, Econometric Theory , 17 , 283-295, 2001
  • (with L.Horvath and G.Teyssiere) Empirical process of squared residuals of an ARCH sequence, The Annals of Statistics , 29 , 445-469, 2001
  • (with L.Giraitis, R.Leipus and G.Teyssiere) Semiparametric estimation of the intensity of long memory in conditional heteroskedasticity, Statistical Inference for Stochastic Processes , 3 , 113-128, 2000
  • (with M.Taqqu) Can one use the Durbin-Levinson algorithm to generate infinite variance fractional ARIMA time series?, Journal of Time Series Analysis , 22 , pp. 317-337, 2001
  • (with M.Csorgo and L.Horvath) Approximations for bootsrapped empirical processes, Proceedings of the American Mathematical Society, 128 , 2457-2464, 2000
  • (with L.Horvath and J.Steinebach) Approximations for weighted bootstrap processes with an application, Statistics and Probability Letters, 48, 59-70, 2000
  • (with T. Mikosch) The periodogram at the Fourier frequencies, Stochastic Processes and their Applications, 86, 49-80, 2000
  • (with L.Giraitis and R.Leipus) Stationary ARCH models: dependence structure and Central Limit Theorem , Econometric Theory, 16, 3-22, 2000
  • (with R.Leipus) Change-point estimation in ARCH models , Bernoulli, 6(3), 513-539, 2000
  • (with M.Taqqu) Discrete time parametric models with long memory and infinite variance, Mathematical and Computer Modelling, 29 , 203--215, 1999
  • (with R.Leipus) Testing for parameter changes in ARCH models Lithuanian Mathematical Journal, 39, , 231-247, 1999
  • (with L.Horvath and J.Steinebach) Testing for changes in multivariate dependent observations with an application to temperature changes, Journal of Multivariate Analysis, 68 , 96-119, 1999 pdf file
  • (with R.Leipus) Change--point in the mean of dependent observations, Statistics and Probability Letters, 40, 385--393, 1998
  • (with T.Mikosch) The integrated periodogram for long memory processes with finite or infinite variance, Stochastic Processes and their Applications, 66, 55-78, 1997
  • (with M.Taqqu) The asymptotic behavior of quadratic forms in strongly dependent heavy-tailed random variables, Stochastic Processes and their Applications, 66 , 21-40, 1997
  • (with L.Horvath) The effect of long-range dependence on change point estimators, Journal of Statistical Planning and Inference, 64 , 57-81, 1997
  • (with M.Taqqu) Parameter estimation for fractional ARIMA with infinite variance innovations, The Annals of Statistics, 24 , No. 5, 1880-1913, 1996
  • Estimation of the mean of an infinite variance AR(1) sequence, Bulletin of the Polish Academy of Sciences, Vol. 44, No. 2, 1996
  • Prediction of infinite variance fractional ARIMA, Probability and Mathematical Statistics, 16.1 , 65-83, 1996
  • (with M.Taqqu) A characterization of mixing processes of type G, Journal of Theoretical Probability, Vol. 9, No. 1, 3-17, 1996
  • (with M.Taqqu) Infinite variance stable moving averages with long memory, Journal of Econometrics, 73, 79-99, 1996
  • (with M.Taqqu) Fractional ARIMA with stable innovations, Stochastic Processes and their Applications, 60, 19-47, 1995

    Papers in collections and proceedings

  • O. Gromenko and P. Kokoszka, Estimation and testing for geostatistical functional data. In: Recent Advances in Functional Data Analysis and Related Topics F. Ferraty, ed., Physica-Verlag, 2011
  • R. Bhansali, M. Holland and P. Kokoszka, Intermittency, long memory and financial returns. In: Long Memory in Economics A. Kirman and G. Teyssiere, eds., Springer, 2005
  • I. Berkes, L. Horvath and P. Kokoszka, Probabilistic and statistical properties of GARCH processes In: Asymptotic Methods in Stochastics: Festschrift for Miklós Csörgö (eds. L. Horvath and B. Szyszkowicz), 409-429, Fields Institute Communications, Volume: 44, American Mathematical Society, 2004
  • R. Bhansali, M. Holland and P. Kokoszka, Chaotic maps with slowly decaying correlations and intermittency In: Asymptotic Methods in Stochastics: Festschrift for Miklós Csörgö (eds. L. Horvath and B. Szyszkowicz), 99-126, Fields Institute Communications, Volume: 44, American Mathematical Society, 2004
  • R. Bhansali and P. Kokoszka, Prediction of long memory time series: a tutorial review In "Processes with Long-Range Correlations" (eds. G. Rangarajan and M. Ding), 3-21, Springer Verlag, 2004
  • P. Kokoszka, G. Teyssiere and A. Zhang, Confidence intervals for the autocorrelations of the squares of GARCH sequences, In "Computational Science - ICCS 2004." Lecture Notes in Computer Science, vol 3039, 837-844, Springer Verlag, 2004
  • P. Kokoszka and A. Parfionovas, Bootstrap unit root tests for heavy-tailed time series In: Handbook of Computational and Numerical Methods in Finance , 175-197, S. Rachev, Ed. Birkhauser, 2004
  • L. Horvath, A. Jach and P. Kokoszka, Change point detection based on empirical quantiles Proceedings of the 4th International Conference on Statistical Data Analysis based on the L_1-norm and Related Methods Y. Dodge, Ed. 229-240, 2002
  • R. Bhansali and P. Kokoszka, Prediction of long memory time series, In: Long-range Dependence: Theory and Applications P. Doukhan, G. Oppenheim and M. S. Taqqu, eds. pp. 355-367, Birkhauser, Boston, 2002
  • P. Kokoszka and R. Leipus, Detection and estimation of changes in regime, In: Long-range Dependence: Theory and Applications P. Doukhan, G. Oppenheim and M. S. Taqqu, eds. pp. 325-337, Birkhauser, Boston, 2002
  • R. Bhansali and P. Kokoszka, Estimation of the long-memory parameter: a review of recent developments and an extension, Proceedings of the Symposium on Inference for Stochastic Processes, I.V. Basawa, C.C.Heyde and R.L. Taylor, eds. IMS Lecture Notes, 125-150, 2001