2025
1. J. Woźny, P. Jaworski, D. Jelito, M. Pitera, A. Wyłomańska: Gaussian dependence structure pairwise goodness-of-fit testing based on conditional covariance and the 20/60/20 rule, Journal of Multivariate Analysis 206, 105396, 2025
2. A. Michalak, J. Hebda-Sobkowicz, J. Wodecki, K. Szabat, M. Wolkiewicz, S. Weisse, J. Valire, R. Zimroz, A. Wyłomańska: Enhancement of cyclic spectral coherence map by statistical testing approach—application to bearing faults diagnosis in electric motors, Meas. Sci. Technol. 36, 016169, 2025
3. A. Drewnicka, A. Michalak, R. Zimroz, A. Kumar, A. Wyłomańska, J. Wodecki: A method for signal components identification in acoustic signal with non-Gaussian background noise using clustering of data in time-frequency domain, Applied Aoustics 23, 110423, 2025
4. D. Kuzio, R. Zimroz, A. Wyłomańska: A modified gamma process for RUL prediction based on data with time-varying heavy-tailed distribution, Information Science 690, 121603, 2025
5. D. Kuzio, R. Zimroz, A. Wyłomańska: A procedure for assessing of machine health index data prediction quality, Measurement 240, 116040, 2025
6. H. Woszczek, A. Chechkin, A. Wyłomańska: Scaled Brownian motion with random anomalous diffusion exponent, Communications in Nonlinear Science and Numerical Simulation 140(1), 108388, 2025
7. J. Janczura, W. Żuławiński, H. Shiri, T. Barszcz, R. Zimroz, A. Wyłomańska: Prediction of machine state for non-Gaussian degradation model using Hidden Markov Model approach, Eksploatacja i Niezawodnosc – Maintenance and Reliability 2025: 27(2), 2025
8. J. Witulska, A. Zaleska, N. Kremzer-Osiadacz, A. Wyłomańska, I. Jabłoński: Robust variance estimators in application to segmentation of measurement data distorted by impulsive and non-Gaussian noise, Measurement 239, 115472, 2025
2024
9. W. Żuławiński, A. Wyłomańska: Errors-in-variables-based methodology of estimation and testing for infinite-variance periodic autoregressive models with additive noise, 32nd European Signal Processing Conference (EUSIPCO), Lyon, France, pp. 1087-1091, 2024
10. K. Skowronek, R. Zimroz, A. Wyłomańska: Testing for finite variance with applications to vibration signals from rotating machines, J. Math. Industry 14(19), 2024
11. A. Pacheco-Pozo, M. Balcerek, A. Wyłomańska, K. Burnecki, I. M. Sokolov, D. Krapf: Langevin equation in heterogeneous landscapes: how to choose the interpretation, Phys. Rev. Lett. 133, 067102, 2024
12. K. Skowronek, M. Arendarczyk, R. Zimroz, A. Wyłomańska: Modified Greenwood statistic and its application for statistical testing, Journal of Computational and Applied Mathematics 452, 116122, 2024
13. A. M. Sathe, N. S. Upadhye, A. Wyłomańska: Forecasting multidimensional autoregressive time series model with symmetric alpha-stable noise using artificial neural networks, Statistical Methods & Applications 33, 783–805, 2024
14. W. Żuławiński, J. Antoni, R, Zimroz, A. Wyłomańska: Robust coherent and incoherent statistics for detection of hidden periodicity in models with non-Gaussian additive noise, EURASIP J. Adv. Signal Process. 71, 2024
15. K. Pączek, D. Jelito, M. Pitera, A. Wyłomańska: Goodness-of-fit tests for the one-sided Levy distribution based on quantile conditional moments, Journal of Applied Statistics 51(15), 3154–3177, 2024
16. H. Shiri, P. Zimroz, A. Wyłomańska, R. Zimroz: Estimating of machinery’s remaining useful life in the presence of non-Gaussian noise by using a robust extended Kalman filter, Measurement 235, 114882, 2024
17. M. Skowron, O. Frankiewicz, J. Jarosz, M. Wolkiewicz, M. Dybkowski, S. Weisse, J. Valire, A. Wyłomańska, R. Zimroz, K. Szabat: Detection and Classification of Rolling Bearing Defects Using Direct Signal Processing with Deep Convolutional Neural Network, Electronics 13(9), 1722, 2024
18. M. Skowron, S. Olszewski, M. Dybkowski, J. Jarosz, M. Pawlak, S. Weisse, J. Valire, A. Wyłomańska, R. Zimroz, K. Szabat: Applications of the TL-Based Fault Diagnostic System for the Capacitor in Hybrid Aircraft, Electronics 13(9), 1638, 2024
19. K. Pączek, D. Jelito, M. Pitera, A. Wyłomańska: Estimation of stability index for symmetric alpha-stable distribution using quantile conditional variance ratios, TEST 33, 297–334, 2024
20. A. Grzesiek, J. Gajda, S. Thapa, A. Wyłomańska: Distinguishing between fractional Brownian motion with random and constant Hurst exponent using sample autocovariance-based statistics, Chaos 34, 043154, 2024
21. D. Dulas, J. Witulska, A. Wyłomańska, I. Jabłoński, K. Walkowiak: Data driven model as a digital twin recommender for sliced 5G network dimensioning and planning, featured with forecast and "what-if" analysis, IEEE Access 12, 50067-50082, 2024
22. W. Żuławiński, J. Antoni, R. Zimroz, A. Wyłomańska: Applications of robust statistics for cyclostationarity detection in non-Gaussian signals for local damage detection in bearings, Mechanical Systems and Signal Processing 214, 111367, 2024
23. W. Żuławiński, P. Kruczek, A. Wyłomańska: Alternative dependency measures-based approach for estimation of the alpha-stable periodic autoregressive model,Communications in Statistics - Simulation and Computation 53(3), 1188-1215, 2024
24. A. Michalak, R. Zdunek, R. Zimroz, A. Wylomanska: Influence of alpha-stable noise on the effectiveness of non-negative matrix factorization – simulations and real data analysis, Electronics 13(5), 829, 2024
25. J. Janczura, A. Puć, Ł. Bielak, A. Wyłomańska: Product of bi-dimensional VAR(1) model components. An application to the cost of electricity load prediction errors Statistics & Risk Modeling 41 (1/2) 1-26, 2024
26. M. Gabor, R. Zdunek, R. Zimroz, A. Wyłomańska: Bearing damage detection with orthogonal and non-negative low-rank feature extraction, IEEE Transactions on Industrial Informatics 20(2), 2944-2955, 2024
2023
27. M. Gabor, R. Zdunek, R. Zimroz, A. Wyłomańska: Non-negative matrix underapproximation as optimal frequency band selector, In: IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society. [Danvers, MA]: IEEE, 1-6, 2023
28. W. Żuławiński, A. Wyłomańska: Empirical study of periodic autoregressive models with additive noise - estimation and testing, Communications in Statistics - Simulation and Computation, 1-26, 2023, doi: 10.1080/03610918.2023.2286217
29. W. Żuławiński, R. Zimroz, A. Wyłomańska: Yule-Walker-Based Approaches for Estimation of Noise-Corrupted Periodic Autoregressive Model - Finite- and Infinite-Variance Cases, 31st European Signal Processing Conference (EUSIPCO), Helisinki, Finland, pp. 1978-1982, 2023
30. A. Kwiatkowski, O. Sobolewski, A. Wyłomańska, M. Sawicki, P. Zieleń, A. Druszcz, M. Ptak: Development of Artificial Intelligence Algorithms to Analyse Weather Conditions for the Prediction of Cerebrovascular Accidents, In: H. Podbielska and M. Kapalla (eds) Predictive, Preventive, and Personalised Medicine: From Bench to Bedside, pp. 283-304, Springer, Cham, 2023
31. M. Balcerek, A. Wyłomańska, K. Burnecki, R. Metzler, D. Krapf: Modelling intermittent anomalous diffusion with switching fractional Brownian motion, New J. Phys. 25 103031, 2023
32. H. Shiri, P. Zimroz, J. Wodecki, A. Wyłomańska, R. Zimroz: Data-driven segmentation of long term condition monitoring data in the presence of heavy-tailed distributed noise with finite-variance, Mechanical Systems and Signal Processing 205, 110833, 2023
33. H. Woszczek, A. Wyłomańska: Autoregressive model with double Pareto distributed noise, Mathematica Applicanda 51(1), 121-141, 2023
34. K. Maraj-Zygmąt, W. Żuławiński, T. Barszcz, R. Zimroz, A. Wyłomańska: Threshold lines identification for non-Gaussian distributed diagnostic features, Measurement 221(15), 113495, 2023
35. W. Wang, M. Balcerek, K. Burnecki, A. V. Chechkin, S.Janusonis, J. Ślęzak, T. Vojta, A. Wyłomańska, and R. Metzler: Memory-multi-fractional Brownian motion with continuous correlations, Phys. Rev. Research 5, L032025, 2023
36. J. Janczura, T. Barszcz, R. Zimroz, A. Wyłomańska: Machine condition change detection based on data segmentation using a three-regime, -stable Hidden Markov Model, Measurement 220, 113399, 2023
37. K. Maraj-Zygmąt, A. Grzesiek, G. Sikora, J. Gajda, A. Wyłomańska: Testing of two-dimensional Gaussian processes by sample cross-covariance function, Chaos 33, 073135, 2023
38. D. Kuzio, R. Zimroz, A. Wyłomańska: Identification of fault frequency variation in the envelope spectrum in the vibration-based local damage detection in changing load/speed conditions, Measurement 218(15), 113148, 2023
39. H. Shiri, P. Zimroz, J. Wodecki, A. Wyłomańska, R. Zimroz, K. Szabat: Using long-term condition monitoring data with non-Gaussian noise for online diagnostics, Mechanical Systems and Signal Processing 200(1), 110472, 2023
40. D. Szarek, I. Jabłoński, R. Zimroz, A. Wyłomańska: Non-Gaussian feature distribution forecasting based on ConvLSTM neural network and its application to robust machine condition prognosis, Expert Systems with Applications 230(15), 120588, 2023
41. K. Skowronek, T. Barszcz, J. Antoni, R. Zimroz, A. Wyłomańska: Assessment of background noise properties in time and time-frequency domains in the context of vibration-based local damage detection in real environment, Mechanical Systems and Signal Processing 199(15), 110465, 2023
42. M.Gabor, R. Zdunek, R. Zimroz, J. Wodecki, A. Wyłomańska: Non-negative tensor factorization for vibration-based local damage detection, Mechanical Systems and Signal Processing 198, 110430, 2023
43. M. Dhull, A. Kumar, A. Wyłomańska: The expectation-maximization algorithm for autoregressive models with normal inverse Gaussian innovations, Communications in Statistics - Simulation and Computation 53(11), 5421–5441, 2023
44. W. Żuławiński, A. Grzesiek, R. Zimroz, A. Wyłomańska: Identification and validation of periodic autoregressive model with additive noise: finite-variance case, Journal of Computational and Applied Mathematics 427, 115131, 2023
45. J. Gajda, A. Grzesiek, A. Wyłomańska: Ornstein - Uhlenbeck process driven by alpha-stable process and its Gamma subordination, Methodology and Computing in Applied Probability 25,9, 2023
46. K. Maraj-Zygmąt, G. Sikora, M. Pitera, A. Wyłomańska: Goodness-of-fit test for stochastic processes using even empirical moments statistic, Chaos 33, 013128, 2023
47. A. M. Sathe, N. S. Upadhye, A. Wyłomańska: Forecasting of symmetric alpha-stable autoregressive models by time series approach supported by artificial neural networks, Journal of Computational and Applied Mathematics 425, 115051, 2023
48. W. Żuławiński, K. Maraj-Zygmąt, H. Shiri, R. Zimroz, A. Wyłomańska: Framework for stochastic modelling of long-term non-homogenous data with non-Gaussian characteristics for machine condition prognosis, Mechanical Systems and Signal Processing 184, 109677, 2023
49. P. Giri, A. Grzesiek, W. Żuławiński, S. Sundar, A. Wyłomańska: The modified Yule-Walker method for multidimensional infinite-variance periodic autoregressive model of order 1, Journal of the Korean Statistical Society 52, 462–493, 2023
2022
50. J. Witulska, A. Wyłomańska: Identification of the structure break point for independent data with changing variance, Mathematica Applicanda 50(1), 65-106, 2022
51. J. Adamska, L. Bielak, J. Janczura, A. Wyłomańska: From Multi- to Univariate: A Product Random Variable with an Application to Electricity Market Transactions: Pareto and Student’s t-Distribution Case, Mathematics 10(18), 3371, 2021
52. M. Balcerek, K. Burnecki, S. Thapa, A. Wyłomańska, A. Chechkin: Fractional Brownian motion with random Hurst exponent: accelerating diffusion and persistence transitions, Chaos 32, 093114, 2022
53. D. Szarek, I. Jabłoński, D. Krapf, A. Wyłomańska: Multifractional Brownian motion characterization based on Hurst exponent estimation and statistical learning, Chaos 32, 083148, 2022
54. F. Moosavi, H. Shiri, J. Wodecki, A. Wyłomańska, R. Zimroz: Application of machine learning tools for long-term diagnostic feature data segmentation, Appl. Sci. 2022, 12(13), 6766, 2022
55. A. Wyłomańska: Statistical tools for anomaly detection as a part of predictive maintenance in the mining industry, Eur. Math. Soc. Mag. 124, 4–15, 2022
56. J. Hebda-Sobkowicz, R. Zimroz, A. Wyłomańska, J. Antoni: Infogram performance analysis and its enhancement for bearings diagnostics in presence of non-Gaussian noise, Mechanical Systems and Signal Processing 170, 108764, 2022
57. D. Szarek, K. Maraj-Zygmąt, G. Sikora, D. Kraft, A. Wyłomańska: Statistical test for anomalous diffusion based on empirical anomaly measure for Gaussian processes, Computational Statistics & Data Analysis 168, 107401, 2022
58. M. Pitera, A. Chechkin, A. Wyłomańska: Goodness-of-fit test for alpha-stable distribution based on the quantile conditional variance statistics, Statistical Methods & Applications 31, 87–424, 2022
2021
59. A. Grzesiek, M. Mrozinska, P. Giri, S. Sundar, A. Wyłomańska: The covariation-based Yule-Walker method for multidimensional autoregressive time series with alpha-stable distributed noise , Int J Adv Eng Sci Appl Math 13, 13, 394–414, 2021
60. A Wyłomańska, J. Gajda, Sundar S. (Issue editors) International Journal of Advances in Engineering Sciences and Applied Mathematics, SI Time Series Modelling, Data Science and Statistical Learning ,Springer, 2021
61. A. Grzesiek, K. Gąsior, A. Wyłomańska, R. Zimroz: Divergence-based segmentation algorithm for heavy-tailed acoustic signals with time-varying characteristics, Sensors 21(24), 8487, 2021
62. T. Moroń, B. Staruch, B. Staruch, S. Tomaszewski, A. Wyłomańska: The Seismic Shock Prediction Algorithm based on the Rock Mass behaviour data, Mathematics in Industry Reports, 2021
63. P. Giri, S. Sundar, A. Wyłomańska: Fractional lower order covariance (FLOC) based estimation for multidimensional PAR(1) model with alpha−stable noise, Int J Adv Eng Sci Appl Math 13, 215–235, 2021
64. J. Gajda, A. Wyłomańska: Asymptotic behavior of dependence measures for Ornstein-Uhlenbeck model based on long memory processes, Int J Adv Eng Sci Appl Math 13, 148–162, 2021
65. W. Żuławiński, A. Wyłomańska: New estimation method for periodic autoregressive time series of order 1 with additive noise, Int J Adv Eng Sci Appl Math 13, 163–176, 2021
66. E. Broszkiewicz-Suwaj, A. Wyłomańska: Application of non-Gaussian multidimensional autoregressive model for climate data prediction, Int J Adv Eng Sci Appl Math 13, 236–247, 2021
67. M. Markiewicz, A. Wyłomańska: Time series forecasting - problem of heavy-tailed distributed noise, Int J Adv Eng Sci Appl Math 13, 248–256, 2021
68. Ł. Bielak, A. Grzesiek, J. Janczura, A. Wyłomańska: Market risk factors analysis for an international mining company. Multi-dimensional heavy-tailed-based modelling, Resources Policy 74, 102308, 2021
69. A. Grzesiek, R. Zimroz, P. Śliwiński, A. Wyłomańska, N. Gomolla: A method for structure break point detection in engine oil pressure data, Energies 14(17), 5496, 2021
70. J. Hebda-Sobkowicz, J. Nowicki, R. Zimroz, A. Wyłomańska: Alternative measures of dependence for cyclic behaviour identification in the signal with impulsive noise - application to the local damage detection, Electronics 10(15), 1863, 2021
71. F. Chaari, J. Leśkow, A Wyłomańska, R. Zimroz, A. Napolitano (Editors) Nonstationary Systems: Theory and Applications,Springer, 2021
72. A. Grzesiek, A. Wyłomańska: Asymptotics of alternative dependence measures for two-dimensional alpha−stable AR(1) model,In: Chaari F. et al. (eds) Nonstationary Systems: Theory and Applications. WNSTA 2021. Applied Condition Monitoring, vol 18., 41-68, Springer, Cham. https://doi.org/10.1007/978-3-030-82110-4_3
73. K. Maraj, A. Wyłomańska: Time-averaged statistics-based methods for anomalous diffusive exponent estimation, In: Chaari F. et al. (eds) Nonstationary Systems: Theory and Applications. WNSTA 2021. Applied Condition Monitoring, vol 18., 1-18, Springer, Cham. https://doi.org/10.1007/978-3-030-82110-4_1
74. A. Grzesiek, A. Michalak, A. Wyłomańska: How to describe the linear dependence for heavy-tailed distributed data,In: Chaari F. et al. (eds) Nonstationary Systems: Theory and Applications. WNSTA 2021. Applied Condition Monitoring, vol 18, 69-92, Springer, Cham. https://doi.org/10.1007/978-3-030-82110-4_4 2020
75. D. Szarek, L. Bielak, A. Wyłomańska: Non-Gaussian regime-switching model in application to the commodity price description, In: Chaari F.et al. (eds) Nonstationary Systems: Theory and Applications. WNSTA 2021. Applied Condition Monitoring, vol 18., 108-126, Springer, Cham. https://doi.org/10.1007/978-3-030-82110-4_6
76. K. Maraj, D. Szarek, G. Sikora, A. Wyłomańska: Time averaged mean squared displacements ratio test for Gaussian processes with unknown diffusion coefficient, Chaos 31, 073120, 2021
77. M. Balcerek, K. Burnecki, G. Sikora, A. Wyłomańska: Discriminating Gaussian processes via quadratic form statistics, Chaos 31, 063101, 2021
78. A. Grzesiek, R. Poloczanski, A. Kumar, A. Wyłomańska: Moment-based estimation technique for parameters of general inverse subordinator , Physica A 575, 126042, 2021
79. P. Kruczek, R. Zimroz, J. Antoni, A. Wyłomańska: Generalized Spectral Coherence for cyclostationary signals with alpha−stable distribution, Mechanical Systems and Signal Processing 159, 107737, 2021
80. J. Nowicki, J. Hebda-Sobkowicz, R. Zimroz, A. Wyłomańska: The application of dependency measures for the selection of the informative frequency band and detection of cyclic impulsive behavior in a vibration signal with heavy-tailed noise, Applied Acoustics 178, 107974, 2021
81. S. Thapa, A. Wyłomańska, G. Sikora, C. E. Wagner, D. Krapf, H. Kantz, A. V. Chechkin, R. Metzler: Leveraging large-deviation statistics to decipher the stochastic properties of measured trajectories, New J. Phys. 23, 013008, 2021
82. A. Michalak, J. Wodecki, M. Drozda, A. Wyłomańska, R. Zimroz: Model of the Vibration Signal of the Vibrating Sieving Screen Suspension for Condition Monitoring Purpose, Sensors 21(1), 213, 2021
83. K. Maraj, D. Szarek, G. Sikora, A. Wyłomańska: Empirical anomaly measure for finite-variance processes, J. Phys. A: Math. Theor. 54, 024001, 2021
84. J. Wodecki, A. Michalak, A. Wyłomańska, R. Zimroz: Influence of non-Gaussian noise on the effectiveness of cyclostationary analysis-simulations and real data case study analysis, Measurement 171, 108814, 2021
2020
85. P. Stępniak, A. Wyłomańska: The maximum likelihood method for Student's t-distributed autoregressive model with infinite variance, Mathematica Applicanda 48(2) 133–15, 2020
86. A. Grzesiek, A. Wyłomańska: Asymptotic behavior of cross-dependence measures for bidimensional AR(1) model with alpha−stable noise, Banach Center Publications 122, 133-157, 2020
87. D. Szarek, G. Sikora, M. Balcerek, I. Jabłoński, A. Wyłomańska: Fractional dynamics identification via intelligent unpacking of the sample autocovariance function by neural networks, Entropy 22(11), 1322, 2020
88. J. Nowicki, J. Hebda-Sobkowicz, R. Zimroz, A. Wyłomańska: Local defect detection in bearings in the presence of heavy-tailed noise and spectral overlapping of informative and non-informative impulses, Sensors 20(22), 6444, 2020
89. K. Maraj, D. Szarek, G. Sikora, M. Balcerek, A. Wyłomańska, I. Jabłoński: Measurement instrumentation and selected signal processing techniques for anomalous diffusion analysis, Measurement: Sensors 6-7, 100017 2020
90. K. Gąsior, H. Urbańska, A. Grzesiek, R. Zimroz, A. Wyłomańska: Identification, decomposition and segmentation of impulsive vibration signals with deterministic components, Sensors 20(19), 5648, 2020
91. A. Grzesiek, P. Giri, S. Sundar, A. Wyłomańska: Measures of cross-dependence for bidimensional periodic AR(1) model with alpha−stable distribution, Journal of Time Series Analysis 41(6), 785-807, 2020
92. A. Grzesiek, R. Zimoroz, P. Śliwiński, N. Gomolla, A. Wyłomańska: A long term belt conveyor temperature data analysis - statistical tests for anomaly detection, Measurement 165, 108124, 2020
93. T. Serafin, A. Michalak, L. Bielak, A. Wyłomańska: Averaged calibration length prediction for currency exchange rates by a time-dependent Vasicek model, Theor. Econ. Lett. 10(3), 579-599, 2020
94. A. Wyłomańska, D. Robert Iskander, K. Burnecki : Omnibus test for normality based on the Edgeworth expansion , PLoSONE 15(6):e0233901, 2020, https://doi.org/10.1371/journal.pone.0233901
95. D. Szarek, L. Bielak, A. Wyłomańska: Long-term prediction of the metals’ prices using non-Gaussian time-inhomogeneous stochastic process, Physica A 555, 124659, 2020
96. J. Hebda-Sobkowicz, R. Zimroz, M. Pitera, A. Wyłomańska: Informative frequency band selection in the presence of non-Gaussian noise - a novel approach based on the conditional variance statistic , Mechnical Systems and Signal Processing 145, 106971, 2020
97. J. Wodecki, A. Michalak, R. Zimroz, A. Wyłomańska: Separation of multiple local-damage-related components from vibration data using Nonnegative Matrix Factorization and multichannel data fusion, Mechanical Systems and Signal Processing 145, 106954, 2020
98. M. Worsa-Kozak, R. Zimroz, A. Michalak,C. Wolkersdorfer, A. Wyłomańska, M. Kowalczyk: Groundwater Level Fluctuation Analysis in a Semi-Urban Area Using Statistical Methods and Data Mining Techniques—A Case Study in Wrocław, Poland, Applied Science 10(10), 3553, 2020
99. J. Hebda-Sobkowicz, R. Zimroz, A. Wyłomańska: Selection of the informative frequency band ina bearing fault diagnosis in the presence of the non-Gaussian noise - comparison of recently developed methods, Applied Science 10, 2657, 2020
100. G. Sikora, M. Hoell, J. Gajda, H. Kantz, A. Chechkin, A. Wyłomańska: Probabilistic properties of detrended fluctuation analysis for Gaussian processes, Phys. Rev. E 101, 032114, 2020
101. P. Kruczek, R. Zimroz, A. Wyłomańska: How to detect the cyclostationarity in heavy-tailed distributed signals, Signal Processing 172, 107514, 2020
102. A. Grzesiek, M. Teuerle, G. Sikora, A. Wyłomańska: Spatio-temporal dependence measures for alpha-stable bivariate AR(1) models , Journal of Time Series Analysis 41(3), 454--475, 2020
103. A. Grzesiek, M. Teuerle, A. Wylomanska:Cross-codifference for bidimensional VAR(1) time series with infinite variance, Communications in Statistics - Simulation and Computation 2020, https://doi.org/10.1080/03610918.2019.1670840
104. Chaari, F., Leskow, J., Zimroz, R., Wylomanska, A., Dudek, A. (Editors): Applied Condition Monitoring. Cyclostationarity: Theory and Methods - IV, Applied Condition Monitoring, vol 16. Springer, Cham, 2020
105. A. Grzesiek, A. Wyłomańska: Subordinated Processes with Infinite Variance, In: Chaari F., Leskow J., Zimroz R., Wyłomańska A., Dudek A. (eds) Cyclostationarity: Theory and Methods – IV. CSTA 2017. Applied Condition Monitoring, vol 16, 111-135, Springer, Cham, 2020
106. P. Poczynek, P. Kruczek, A. Wyłomańska: Ornstein-Uhlenbeck Process Delayed by Gamma Subordinator , In: Chaari F., Leskow J., Zimroz R., Wyłomańska A., Dudek A. (eds) Cyclostationarity: Theory and Methods – IV. CSTA 2017. Applied Condition Monitoring, vol 16, 147-165, Springer, Cham, 2020
107. A. Michalak, J. Wodecki, A. Wyłomańska, R. Zimroz: Influence of Signal to Noise Ratio on the Effectiveness of Cointegration Analysis for Vibration Signal , In: Chaari F., Leskow J., Zimroz R., Wyłomańska A., Dudek A. (eds) Cyclostationarity: Theory and Methods – IV. CSTA 2017. Applied Condition Monitoring, vol 16, 136-146, Springer, Cham, 2020
108. J. Wodecki, A. Michalak, P. Stefaniak, A. Wyłomańska, Radosław Zimroz: Combination of Kolmogorov-Smirnov Statistic and Time-Frequency Representation for P-Wave Arrival Detection in Seismic Signal , In: Chaari F., Leskow J., Zimroz R., Wyłomańska A., Dudek A. (eds) Cyclostationarity: Theory and Methods – IV. CSTA 2017. Applied Condition Monitoring, vol 16, 166-174, Springer, Cham, 2020
2019
109. A. Grzesiek, S. Sundar, A. Wylomanska, : Fractional lower order covariance-based estimator for bidimensional AR(1) model with stable distribution, International Journal of Advances in Engineering Sciences and Applied Mathematics 11(3), 217-229, 2019
110. P. Kruczek, W. Żuławiński, P. Pagacz, A. Wyłomańska: Fractional lower order covariance based-estimator forOrnstein-Uhlenbeck process with stable distribution, Mathematica Applicanda 47, 259-292, 2019
111. J. Wodecki, J. Hebda-Sobkowicz, A. Mirek, R. Zimroz, A. Wyłomańska: Combination of principal component analysis and time-frequency representation for P-wave arrival detection, Shock and Vibration Volume 2019, Article ID 5961073, 7 pages
112. M. Szmigiel, A. Grzesiek, A. Wyłomańska, H. Kasprzak: Stable distribution in application to fixational eye movement description, Optica Applicata 49 (2), 365-377, 2019
113. J. Hebda-Sobkowicz, R. Zimroz, S. Gola, A. Wylomanska: Identification and Statistical Analysis of Impulse-Like Patterns of Carbon Monoxide Variation in Deep Underground Mines Associated with the Blasting Procedure, Sensors 19(12), 2757, 2019
114. Ł. Bielak, P. Miśta, A. Michalak, A. Wyłomańska: The application of correlation models for the analysis of market risk factors in KGHM capital group, Proceedings in Eartch and Geosciences vol. 3, Mining Goes Digital, Mueller et al. (Eds.), 38-46, 2019
115. A. Kumar, A. Maheshwari, A. Wylomanska: Linnik Levy Process and Its Generalization , Physica A 529, 121539, 2019
116. J. Wodecki, P. Kruczek, A. Bartkowiak, R. Zimroz, A. Wylomanska: Novel method of informative frequency band selection for vibration signal using Nonnegative Matrix Factorization of spectrogram matrix, Mechanical Systems and Signal Processing 130, 585-596, 2019
117. G. Sikora, Ł. Bielak, A. Michalak, P. Miśta, A. Wyłomańska: Stochastic modelling of currency exchange rates with novel validation techniques, Physica A 523, 1202-1215, 2019
118. Kumar Arun, Wylomanska Agnieszka, Poloczanski Rafal, Gajda Janusz: Fractional Brownian motion delayed by tempered and inverse tempered stable subordinators, Methodology and Computing in Applied Probability 21(1), 185-202, 2019
119. J. Hebda-Sobkowicz, S. Gola, R. Zimroz, A. Wylomanska: Pattern of H2S concentration in a deep copper mine and its correlation with ventilation schedule, Measurement 140, 373-381, 2019
120. J. Wodecki, A. Michalak, R. Zimroz, T. Barszcz, A. Wyłomańska: Impulsive source separation using combination of Nonnegative Matrix Factorization of bi-frequency map, spatial denoising and Monte Carlo simulation , Mechanical Systems and Signal Processing 127, 89-101, 2019
121. Kumar Arun, Gajda Janusz, Wylomanska Agnieszka: Stable Levy Process Delayed by Tempered Stable Subordinator, Statistics and Probability Letters 145, 284-292, 2019
122. Zak Grzegorz, Wylomanska Agnieszka, Zimroz Radoslaw: Periodically impulsive behaviour detection in noisy observation based on generalised fractional order dependency map, Applied Acoustics 144, 31-39, 2019
123. Michalak Anna, Wodecki Jacek, Wylomanska Agnieszka, Zimroz Radoslaw: Application of cointegration to vibration signal for local damage detection in gearboxes, Applied Acoustics 144, 4-10, 2019
124. Gajda Janusz, Wylomanska Agnieszka, Kumar Arun: Fractional Levy stable motion time-changed by gamma subordinator, Communications in Statistics - Theory and Methods 48, (24), 5953–5968, 2019
125. Kumar Arun, N. S. Upadhye, Wylomanska Agnieszka, Gajda Janusz: Tempered Mittag-Leffler Levy Process, Communications in Statistics - Theory and Methods 48 (2), 396–411, 2019
126. Kruczek Piotr, Obuchowski Jakub, Wylomanska Agnieszka, Zimroz Radoslaw: Multiple local damage detection in gearbox by novel coherent bi-frequency map and its spatial, cycle oriented enhancement, Applied Acoustics 144, 23-30, 2019
127. Sokolowski Jakub, Kruczek Piotr, Wylomanska Agnieszka, Zimroz Radoslaw: Multiple local damage detection method based on time-frequency representation and agglomerative hierarchical clustering of temporary spectral content, Applied Acoustics 147, 44-55, 2019
2018
128. Y. Lanoiselee, D.S. Grebenkov, G. Sikora, A. Grzesiek, A. Wylomanska: Optimal parameters for anomalous diffusion exponent estimation from noisy data , Phys. Rev. E 98, 062139, 2018
129. Zak Grzegorz, Wylomanska Agnieszka, Zimroz Radoslaw: Local damage detection method based on distribution distances applied to time-frequency map of vibration signal, IEEE Transactions on Industry Applications 54(5), 4091- 4103, 2018
130. Janusz Gajda, Agnieszka Wylomanska, Holger Kantz, Aleksei Chechkin, Grzegorz Sikora:Large deviations of time-averaged statistics for Gaussian processes , Statistics and Probability Letters 143, 47-55, 2018
131. Grzegorz Sikora, Agnieszka Wylomanska, Diego Krapf:Recurrence statistics for anomalous diffusion regime change detection , Computational Statistics & Data Analysis 128, 380-394, 2018
132. Kruczek Piotr, Polak Marta, Wylomanska Agnieszka, Kawalec Witold, Zimroz Radoslaw: Application of compound Poisson process for modelling of ore flow in a belt conveyor system with cyclic loading,Journal International Journal of Mining, Reclamation and Environment 32(6), 376-391, 2018
133. Wodecki Jacek, Stefaniak Pawel, Michalak Anna, Wylomanska Agnieszka, Zimroz Radoslaw: Technical condition change detection using Anderson-Darling statistic approach for LHD machines - engine overheating problem,Journal International Journal of Mining, Reclamation and Environment 32(6), 392-400, 2018
134. Aleksandra Grzesiek, Janusz Gajda, Agnieszka Wylomanska, S. Sundar: Discriminating between scaled and fractional Brownian motion via p-variation statistics, International Journal of Advances in Engineering Sciences and Applied Mathematics 10(1), 9-14, 2018
135. Kucharczyk Daniel, Wylomanska Agnieszka, Sikora Grzegorz: Variance change point detection for fractional Brownian motion based on the likelihood ratio test, Physica A 490, 439-450, 2018
136. Andrzej Szczurek, Monika Maciejewska, Agnieszka Wylomanska, Michal Balcerek, Grzegrz Sikora, Marek Teuerle:Normal and anomalous diffusion of dust concentration nearby emission source, Physica A 491, 619-631, 2018
2017
137. Sikora Grzegorz, Wylomanska Agnieszka, Gajda Janusz, Laura Sole, Elizabeth J. Akin, Michael M. Tamkun, Diego Krapf: Elucidating distinct ion channel populations on the surface of hippocampal neurons via single-particle tracking recurrence analysis, Phys. Rev. E 96, 062404, 2017
138. Zak Grzegorz, Wylomanska Agnieszka, Zimroz Radoslaw: Data driven iterative vibration signal enhancement strategy using alpha stable distribution, Shock and Vibration, vol. 2017, Article ID 3698370, 11 pages, 2017. doi:10.1155/2017/3698370
139. Zak Grzegorz, Teuerle Marek, Wylomanska Agnieszka, Zimroz Radoslaw: Measures of dependence for alpha-stable distributed processes and its application to diagnostics of local damage in presence of impulsive noise, Shock and Vibration, vol. 2017, Article ID 1963769, 9 pages, 2017. doi:10.1155/2017/1963769
140. Sikora Grzegorz, Teuerle Marek, Wylomanska Agnieszka, Grebenkov Denis: Statistical properties of the anomalous scaling exponent estimator based on time averaged mean square displacement, Phys. Rev. E 96, 022132, 2017
141. Jabłońska Matylda, Teuerle Marek, Wyłomańska Agnieszka: Bivariate sub-Gaussian model for stock indices returns, Physica A 486(15), 628–637, 2017
142. Kruczek Piotr, Obuchowski Jakub, Wylomanska Agnieszka, Zimroz Radoslaw: Cyclic sources extraction from complex multiple-component vibration signal via periodically time varying filter, Applied Acoustics 126, 170-181, 2017
143. Kumar Arun, Wylomanska Agnieszka, Gajda Janusz: Stable Levy motion with inverse Gaussian subordinator, Physica A 482, 486–500, 2017
144. Wodecki Jacek, Zdunek Rafal, Wylomanska Agnieszka, Zimroz Radoslaw: Local fault detection of rolling element bearing components by spectrogram clustering with semi-binary NMF, Diagnostyka 18(1), 3-9, 2017
145. Sikora Grzegorz, Burnecki Krzysztof, Wylomanska Agnieszka: Mean-squared displacement statistical test for fractional Brownian motion, Phys. Rev. E 95, 032110, 2017
146. Piotr Kruczek, Jakub Sokołowski, Jakub Obuchowski, Mateusz Sawicki, Agnieszka Wyłomańska, Radosław Zimroz: Fault Detection in Belt Conveyor Drive Unit via Multiple Source Data, In: Chaari F., Leskow J., Napolitano A., Zimroz R., Wylomanska A. (eds) Cyclostationarity: Theory and Methods III. Applied Condition Monitoring, vol 6. Springer, Cham, pp. 173-186, 2017
147. Malgorzata Wisniewska, Agnieszka Wylomanska: GARCH process with GED distribution, In: Chaari F., Leskow J., Napolitano A., Zimroz R., Wylomanska A. (eds) Cyclostationarity: Theory and Methods III. Applied Condition Monitoring, vol 6. Springer, Cham, pp. 83-103, 2017
148. Marta Polak, Jakub Obuchowski, Agnieszka Wylomanska, Radoslaw Zimroz: Seismic signal enhancement via AR filtering and spatial time-frequency denoising, In: Chaari F., Leskow J., Napolitano A., Zimroz R., Wylomanska A. (eds) Cyclostationarity: Theory and Methods III. Applied Condition Monitoring, vol 6. Springer, Cham, pp. 51-68, 2017
149. Agnieszka Wylomanska, Grzegorz Zak, Piotr Kruczek, Radoslaw Zimroz:Application of tempered stable distribution for selection of optimal frequency band in gearbox local damage detection, Applied Acoustics 128, 14-22, 2017
150. Kumar Arun, Wylomanska Agnieszka, Gajda Janusz: Generalized fractional Laplace motion, Statistics and Probability Letters 124, 101-109, 2017
151. Kucharczyk Daniel, Wylomanska Agnieszka, Zimroz Radoslaw: Structural break detection method based on the Adaptive Regression Splines technique, Physica A 471, 499-511, 2017
152. Rafal Poloczanski, Agnieszka Wylomanska, Janusz Gajda, Monika Maciejewska, Andrzej Szczurek : Modified cumulative distribution function in application to waiting times analysis in CTRW scenario, J. Phys. A: Math. Theor. 50, 034002, 2017
153. Arun Kumar, Agnieszka Wylomanska, Rafal Poloczanski, S. Sundar: Fractional Brownian motion time-changed by gamma and inverse gamma process, Physica A 468, 648–667, 2017
154. Kruczek Piotr, Wylomanska Agnieszka, Teuerle Marek, Gajda Janusz: The modified Yule-Walker method for alpha-stable time series models, Physica A 469, 588–603, 2017
2016
155. Agnieszka Wylomanska, Arun Kumar, Rafal Poloczanksi, Palaniappan Vellaisamy: Inverse Gaussian and its inverse process as the subordinators of fractional Brownian motion, Phys. Rev. E 94, 042128, 2016
156. Jakub Sokolowski, Jakub Obuchowski, Agnieszka Wylomanska, Radoslaw Zimroz, Eugeniusz Koziarz: Algorithm indicating moment of P-wave arrival based on second-moment characteristic,Shock and Vibration vol. 2016 (2016), Article ID 4051701, http://dx.doi.org/10.1155/2016/4051701, 2016
157. Janusz Gajda, Agnieszka Wylomanska, Radoslaw Zimroz: Subordinated continuous-time AR processes and their application to modeling behavior of mechanical system,Physica A 464(15), 123-137, 2016
158. Andrzej Szczurek, Monika Maciejewska, Agnieszka Wylomanska, Grzegorz Sikora, Michal Balcerek, Marek Teuerle: Discrimination of particulate matter emission sources using stochastic methods, Physica A 463, 452-466, 2016
159. Agnieszka Wylomanska, Radoslaw Zimroz, Joanna Janczura, Jakub Obuchowski: Impulsive noise cancellation method for copper ore crusher vibration signals enhancement, IEEE Transactions on Industrial Electronics 63(9), 5612-5621, 2016
160. Andrzej Szczurek, Monika Maciejewska, Agnieszka Wylomanska, Radoslaw Zimroz, Grzegorz Zak, Anna Dolega: Detection of occupancy profile based on carbon dioxide concentration pattern matching, Measurement 93, 265-271, 2016
161. Jakub Sokolowski, Jakub Obuchowski, Maciej Madziarz, Agnieszka Wyłomańska, Radosław Zimroz : Features based on Instantaneous Frequency for seismic signals clustering, Journal of Vibroengineering 18(3), 1654-1667, 2016
162. Daniel Kucharczyk, Agnieszka Wylomanska, Jakub Obuchowski, Radoslaw Zimroz, Maciej Madziarz: Stochastic modelling as a tool for seismic signals segmentation, Shock and Vibration, vol. 2016, Article ID 8453426, 13 pages, 2016, doi:10.1155/2016/8453426
163. Grzegorz Zak, Agnieszka Wyłomańska, Radosław Zimroz : Data-driven vibration signal filtering procedure based on the alpha-stable distribution, Journal of Vibroengineering 18(2), 826-837, 2016
164. Obuchowski Jakub, Zimroz Radoslaw, Wylomanska Agnieszka: Blind equalization using combined skewness-kurtosis criterion for gearbox vibration enhancement, Measurement 88, 34-44, 2016
165. Marta Polak, Jakub Obuchowski, Maciej Madziarz, Agnieszka Wyłomańska, Radosław Zimroz : Time-varying group delay as a basis for clustering and segmentation of seismic signals, Journal of Vibroengineering 18(1), 267-275, 2016
166. Wylomanska Agnieszka, Gajda Janusz: Stable continuous-time autoregressive process driven by stable subordinator, Physica A 444, 1012-1026, 2016
167. Zimroz Radoslaw, Obuchowski Jakub, Wylomanska Agnieszka: Vibration analysis of copper ore crushers used in mineral processing plant - problem of bearings damage detection in presence of heavy impulsive noise , Applied Condition Monitoring. Advances in Condition Monitoring of Machinery in Non-Stationary Operations (Chaari et al. ed.), 57-70, 2016
168. Obuchowski Jakub, Wylomanska Agnieszka, ZImroz Radoslw: New criteria for adaptive blind deconvolution of vibration signals from planetary gearbox, Applied Condition Monitoring. Advances in Condition Monitoring of Machinery in Non-Stationary Operations (Chaari et al. ed.), 111-125, 2016
169. Stefaniak Pawel, Zimroz Radoslaw, Sliwinski Pawel, Andrzejewski Marek, Wylomanska Agnieszka: Multidimensional signal analysis for technical condition, operation and performance understanding of heavy duty mining machines, Applied Condition Monitoring. Advances in Condition Monitoring of Machinery in Non-Stationary Operations (Chaari et al. ed.), 197-210, 2016
170. Stefaniak Pawel, Wylomanska Agnieszka, Zimroz Radoslaw, Barlemus Walter, Hardygora Monika: Diagnostic features modeling for decision boundaries calculation for maintenance of gearboxes used in belt conveyor system Applied Condition Monitoring. Advances in Condition Monitoring of Machinery in Non-Stationary Operations (Chaari et al. ed.), 251-263, 2016
2015
171. Burnecki Krzysztof, Wylomanska Agnieszka, Aleksei Chechkin: Discriminating between light- and heavy-tailed distributions with limit theorem, PLoS ONE 10(12): e0145604. doi:10.1371/journal. pone.0145604, 2015
172. Zak Grzegorz, Wylomanska Agnieszka, Zimroz Radoslaw: Application of alpha-stable distribution approach for local damage detection in rotating machines, Journal of Vibroengineering 17(6), 2987-3002, 2015
173. Radoslaw Zimroz, Maciej Madziarz, Grzegorz Żak, Agnieszka Wyłomańska, Jakub Obuchowski: Seismic signal segmentation procedure using time-frequency decomposition and statistical modelling, Journal of Vibroengineering 17(6), 3111-3121, 2015
174. Mateusz Sawicki, Radoslaw Zimroz, Agnieszka Wyłomańska, Jakub Obuchowski, Pawel Stefaniak, Grzegorz Żak: An automatic procedure for multidimensional temperature signals analysis from SCADA system with application to belt conveyor components,Procedia Earth and Planetary Science 15, 781–790, 2015
175. Wylomanska Agnieszka, Zimroz Radosław, Janczura Joanna: Identification and stochastic modelling of sources in copper ore crusher vibrations, Journal of Physics: Conference Series 628(2015) 012125, 2015
176. Przylibski Tadeusz, Wylomanska Agnieszka, Zimroz Radosław, Fijalkowska-Lichwa Lidia: Application of spectral decomposition of 222RN activity concentration signal series measured in Niedzwiedzia Cave to identification of mechanism responsible for different time-period variations,Applied Radiation and Isotopes 104, 74-86, 2015
177. Obuchowski Jakub, Zimroz Radoslaw, Wylomanska Agnieszka: Identification of cyclic components in presence of non-Gaussian noise – application to crusher bearings damage detection, JVE INTERNATIONAL LTD. JOURNAL OF VIBROENGINEERING 17, 1242-1252, 2015
178. Szczurek Andrzej, Maciejewska Monika, Rafal Poloczanski, Teuerle Marek, Wyłomańska Agnieszka: Dynamics of carbon dioxide concentration in indoor air, Stoch Environ Res Risk Assess. 29 (8), 2193-2199, 2015
179. Chaari, F., Leskow, J., Napolitano, A., Zimroz, R., Wylomanska, A., Dudek, A.: Applied Condition Monitoring. Cyclostationarity: Theory and Methods - II, Springer International Publishing Switzerland, 2015
180. Jabłońska Matylda, Wyłomańska Agnieszka: Multidimensional analysis of New Zealand electricity prices, Applied Condition Monitoring. Cyclostationarity: Theory and Methods - II (Chaari et al. ed.), 155-177, 2015
181. Wyłomańska Agnieszka: The dependence structure for symmetric alpha-stable CARMA(p,q) processes , Applied Condition Monitoring. Cyclostationarity: Theory and Methods - II (Chaari et al. ed.), 189-206, 2015
182. Wyłomańska Agnieszka, Obuchowski Jakub, Zimroz Radosław, Hurd Harry: Influence of different signal characteristics to PAR model stability, Applied Condition Monitoring. Cyclostationarity: Theory and Methods - II (Chaari et al. ed.), 89-104, 2015
183. Gajda Janusz, Wyłomańska Agnieszka: Time-changed Ornstein-Uhlenbeck process, J. Phys. A: Math. Theor. 48 135004, 2015
184. Wyłomańska Agnieszka, Zimroz Radosław: The Analysis of Stochastic Signal from LHD Mining Machine, Stochastic Models, Statistics and Their Applications Springer Proceedings in Mathematics & Statistics Volume 122, 469-478, 2015
185. Jabłońska Matylda, Wyłomańska Agnieszka: Periodic models for hydrological storage reservoir levels. Case Study of New Zealand., Stochastic Models, Statistics and Their Applications Springer Proceedings in Mathematics & Statistics Volume 122, 293-300, 2015
186. Wyłomańska Agnieszka, Chechkin Aleksei, Sokolov Igor M., Gajda Janusz: Codifference as a practical tool to measure interdependence, Physica A 421, 412-429, 2015
187. Szczurek Andrzej, Maciejewska Monika, Teuerle Marek, Wyłomańska Agnieszka: Method to characterize collective impact of factors on indoor air, Physica A 420, 190–-199, 2015
188. Stefaniak Paweł, Wyłomańska Agnieszka, Obuchowski Jakub, Zimroz Radosław: Procedures for decision thresholds finding in maintenance management of belt conveyor system – statistical modeling of diagnostic data, in: Lecture Notes in Production Engineering, Christian Niemann-Delius ed., 391-402, Springer, 2015
189. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: Two-stage data driven filtering for local damage detection in presence of time varying signal to noise ratio, Vibration Engineering and Technology of Machinery Mechanisms and Machine Science Volume 23, 401-410, 2015
2014
190. Zak Grzegorz, Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radoslaw: Application of ARMA modelling and alpha-stable distribution for local damage detection in bearings, Diagnostyka 15(3), 3-11, 2014
191. Zak Grzegorz, Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radoslaw: Novel 2D representation of vibration for local damage detection, Mining Science 21, 105-113, 2014
192. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: Recent developments in vibration based diagnostics of gear and bearings used in belt conveyors, Applied Mechanics and Materials 683, 171-176, 2014
193. Wyłomańska Agnieszka, Zimroz Radosław: Signal segmentation for operational regimes detection of heavy duty mining mobile machines- a statistical approach, Diagnostyka 15(2), 33-42, 2014
194. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: Selection of informative frequency band in local damage detection in rotating machinery, Mechanical Systems and Signal Processing 48, 138--152, 2014
195. Gajda Janusz, Wyłomańska Agnieszka: Fokker-Planck type equations associated with fractional Brownian motion controlled by infinitely divisible processes, Physica A 405, 104--113, 2014
196. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: The local maxima method for enhancement of time-frequency map, Advances in Condition Monitoring of Machinery in Non-Stationary Operations, Lecture Notes in Mechanical Engineering, G. Dalpiaz et al. (eds.), 325-334, 2014
197. Stefaniak Paweł, Wyłomańska Agnieszka, Zimroz Radosław: Procedury wyznaczania progów decyzyjnych w zarzadzaniu eksploatacja układów napędowych przenosników tasmowych -- statystyczne modelowanie danych diagnostycznych, XXIII Szkoła Eksploatacji Podziemnej: materiały konferencyjne, Kraków, 24--28 lutego 2014, 1-11
198. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: The local maxima method for enhancement of time-frequency map and its application to local damage detection in rotating machines, Mechanical Systems and Signal Processing 46, 389--405, 2014
199. Wyłomańska Agnieszka, Obuchowski Jakub, Zimroz Radosław, Harry Hurd: Periodic autoregressive modeling of vibration time series from planetary gearbox used in bucket wheel excavator,in Cyclostationarity: Theory and Methods Lecture Notes in Mechanical Engineering, Fakher Chaari et al. (eds.), 171-186, 2014
2013
200. Wyłomańska Agnieszka: Tempered stable process with infinitely divisible inverse subordinators, J. Stat. Mech. P10011, 2013
201. Janczura Joanna, Teuerle Marek, Wyłomańska Agnieszka: Analiza jakosci powietrza wewnetrznego z wykorzystaniem metod szeregów czasowych, w Czujniki i Sensory do Pomiaru Czynników Stanowiacych Zagrożenia w Srodowisku, czesc 2 red, Waldemar Grzebyk, Wrocław, 2013
202. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: Quantile-based risk measures as a tool for local damage detection in rotating mining machinery, in: Interdyscyplinarne Zagadnienia w Górnictwie i Geologii, red. J. Drzymała, W. Ciężkowski, 159-164, Wrocław 2013
203. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: Selection of informative frequency band based on the local maxima method in application to bearing diagnostics, 12th International Technical Systems Degradation Conference (Liptovský Mikulás, Slovakia, 3-6.04 2013)
204. Teuerle Marek, Wyłomańska Agnieszka, Sikora Grzegorz: Modelling anomalous diffusion by subordinated fractional Levy-stable process, J. Stat. Mech. P05016, 2013
205. Obuchowski Jakub, Wyłomańska Agnieszka, Zimroz Radosław: Stochastic modeling of time series with application to local damage detection in rotating machinery, Damage Assessment of Structures in: Key Engineering Materials 569, 441-449, 2013
206. Obuchowski Jakub, Wyłomańska Agnieszka: The Ornstein-Uhlenbeck process with non-Gaussian structure, Acta Phys. Polon B 44(5), 1123-1136, 2013
207. Gajda Janusz, Sikora Grzegorz, Wyłomańska Agnieszka: Regime variance testing - a quantile approach, Acta Phys. Polon B 44(5), 1015-1035, 2013
208. Maciejewska Monika, Andrzej Szczurek, Joanna Janczura, Wyłomańska Agnieszka: Stochastic modeling of indoor air temperature, J. Stat. Phys. 152, 979-994, 2013
209. Gajda Janusz, Wyłomańska Agnieszka: Tempered stable Levy motion driven by stable subordinator, Physica A 392, 3168-–3176, 2013
2012
210. Maciejewska Monika, Szczurek Andrzej, Grzegorz Sikora, Wyłomańska Agnieszka: Diffusive and subdiffusive dynamics of indoor microclimate. A time series modeling. Phys. Rev. E 86, 031128, 2012
211. Gajda Janusz, Wyłomańska Agnieszka: Geometric Brownian motion with tempered stable waiting times, J. Stat. Phys. 148, 296-305, 2012
212. Burnecki Krzysztof, Wyłomańska Agnieszka, Aleksei Beletskii, Vsevolod Gonchar, Aleksei Chechkin: Recognition of stable distribution with Levy index alpha close to 2, Phys. Rev. E 85, 056711, 2012
213. Wyłomańska Agnieszka: Arithmetic Brownian motion subordinated by tempered stable and inverse tempered stable processes, Physica A 391 (22), 5685-5696, 2012
214. Janczura Joanna, Wyłomańska Agnieszka: Anomalous diffusion models: different types of subordinator distribution, Acta Phys. Polon. B 43(5), 1001-1016, 2012
215. Wyłomańska Agnieszka: How to identify the proper model?, Acta Phys. Polon. B 43(5), 1241-1253, 2012
2011
216. Wyłomańska Agnieszka: Measures of dependence for Ornstein-Uhlenbeck process with tempered stable distribution, Acta Phys. Polon. B 42(10), 2049-2062, 2011
217. Orzeł Sebastian, Wyłomańska Agnieszka: Calibration of the subdiffusive arithmetic Brownian motion with tempered stable waiting-times, J. Stat. Phys. 143(3), 447-454, 2011
218. Janczura Joanna, Orzeł Sebastian, Wyłomańska Agnieszka: Subordinated alpha-stable Ornstein-Uhlenbeck process as a tool of financial data description, Physica A 390, 4379-4387, 2011
2010
219. Węglorz Magdalena, Wyłomańska Agnieszka: Optimal bidding strategies on the power market based on the stochastic models, Proceedings of the Modern Electric Power Systems MEPS'10 International Symposium, September 20-22, 2010, Wrocław, Poland, 2010
2009
220. Janczura Joanna, Wyłomańska Agnieszka: Subdynamics of financial data from fractional Fokker-Planck equation, Acta Phys. Polon. B 40(5), 1341-1351, 2009
221. Jurlewicz Agnieszka, Wyłomańska Agnieszka, Żebrowski Piotr: Coupled continuous-time random walk approach to the Rachev-Ruschendorf model for financial data, Physica A 388, 407-418, 2009
222. Borgosz-Koczwara Magdalena, Weron Aleksander, Wyłomańska Agnieszka: Stochastic models for bidding strategies on oligopoly electricity market, Math. Methods. Oper. Res. 69(3), 579-592, 2009
2008
223. Jurlewicz Agnieszka, Wyłomańska Agnieszka, Żebrowski Piotr: Financial Data Analysis by means of Coupled Continuous-Time Random Walk in Rachev-Ruschendorf Model, Acta Phys. Polon. A 114(3), 629-634, 2008
224. Sapio Sandro, Wyłomańska Agnieszka: The impact of forward trading on the spot power price volatility with Cournot competition, 5th International Conference on the European Electricity Market, EEM08, May 28-30, 2008, Lisbon (doi:10.1109/EEM.2008.4579013)
225. Makagon Andrzej, Wyłomańska Agnieszka: On the support of the spectral measure of a harmonizable sequence, Proceedings of the American Mathematical Society 136(7), 2609-2613, 2008
226. Nowicka-Zagrajek Joanna, Wyłomańska Agnieszka: Measures of dependence for stable AR(1) models with time-varying coefficients, Stochastic Models 24(1), 58-70, 2008
227. Wyłomańska Agnieszka: Spectral measures of PARMA sequences, Journal of Time Series Analysis 29(1), 1-13, 2008
2006
228. Nowicka-Zagrajek Joanna, Wyłomańska Agnieszka: The dependence structure for PARMA models with a-stable innovations, Acta Phys. Polon. B 37(1), 3071-3081, 2006
2005
229. Burnecki Krzysztof, Nowicka-Zagrajek Joanna, Wyłomańska Agnieszka: Pure risk premiums under deductibles, in "Statistical Tools for Finance and Insurance",Springer, Berlin, 427-452, 2005
2004
230. Weron Aleksander, Wyłomańska Agnieszka: On ARMA(1,q) Models with Bounded and Periodically Correlated Solutions, Probability and Mathematical Statistics 24, 165-172, 2004
231. Makagon Andrzej, Weron Aleksander, Wyłomańska Agnieszka: Bounded Solutions of ARMA Models with Varying Coefficients, Applicationes Mathematicae 31(3), 273-285, 2004
232. Broszkiewicz-Suwaj Ewa, Makagon Andrzej, Weron Rafał, Wyłomańska Agnieszka: On detecting and modeling periodic correlation in financial data, Physica A 336, 196-205, 2004

SUBMITTED PAPERS

1. M. Niedźwiecki, A. Gańcza, W. Żuławiński, A. Wyłomańska: Robust local basis function algorithms for identification of time-varying FIR systems in impulsive noise environments, accepted, 2024
2. J. Woźny, P. Jaworski, D. Jelito, M. Pitera, A. Wyłomańska: Gaussian dependence structure pairwise goodness-of-fit testing based on conditional covariance and the 20/60/20 rule, accepted, 2024
3. W. Żuławiński, D. Kuzio, R. Zimroz, A. Wyłomańska: New health indicator based on robust spectral coherence maps for prognosis of degradation process in highly impulsive environment, submitted, 2024
4. A. Michalak, J. Hebda-Sobkowicz, J. Wodecki, M. Dybkowski, M. Wolkiewicz, S. Weisse, J. Valire, K. Szabat, R. Zimroz, A. Wyłomańska: Statistical test for cyclostationarity based on CSC-based indicators - application to vibration signals from electric motor, submitted, 2024
5. M. Yazdanianasr, R. Zimroz, K. Gryllias, A. Wyłomańska: Efficient rolling element bearing fault diagnostics in the presence of highly leptokurtic non-Gaussian noise, submitted, 2024
6. K. Pączek, D. Jelito, M. Pitera, A. Wyłomańska: Conditional correlation estimation and serial dependence identification, submitted, 2024
7. M. Balcerek, A. Pacheco-Pozo, A. Wyłomańska, K. Burnecki, D. Krapf: Two-dimensional Brownian motion with dependent components: turning angle analysis, submitted, 2024
8. D. Kuzio, W. Żuławiński, R. Zimroz, A. Wyłomańska: Development of novel health indicators based on statistical analysis of cyclic spectral coherence maps and their application to local damage detection, submitted, 2024
9. M. Niedźwiecki, A. Gańcza, W. Żuławiński, A. Wyłomańska: Robust suboptimal local basis function algorithms for identification of nonstationary FIR systems in impulsive noise environments, submitted, 2024
10. A. Michalak, J. Hebda-Sobkowicz, J. Wodecki, K. Szabat, M. Wolkiewicz, S. Weisse, J. Valire, R. Zimroz, A. Wyłomańska: Enhancement of cyclic spectral coherence map by statistical testing approach - application to bearing faults diagnosis in electric motors, accepted, 2024
11. K. Skowronek, M. Arendarczyk, A. K. Panorska, T. J. Kozubowski, A. Wyłomańska: Testing and estimation of the index of stability of univariate and bivariate symmetric alpha-stable distributions via modified Greenwood statistic, submitted, 2024
12. H. Woszczek, A. Wyłomańska, A. Chechkin: Riemann-Liouville fractional Brownian motion with random Hurst exponent, submitted, 2024
13. Y. Lanoiselee, G. Pagnini, A. Wyłomańska: Super-resolved anomalous diffusion: deciphering the joint distribution of anomalous exponent and diffusion coefficient, submitted, 2024
14. J. Hebda-Sobkowicz, A. Michalak, J. Wodecki, R. Zimroz, K. Szabat, M. Wolkiewicz, A. Wyłomańska: Advanced spatial processing of the cyclic spectral coherence map and its application to bearing fault detection in electric motors, submitted, 2024
15. A. Napolitano, A. Wyłomańska: Characterization of Irregular Cyclicities in Heavy-Tailed Data, submitted, 2024
16. M. Balcerek, S. Thapa, K. Burnecki, H. Kantz, R. Metzler, A. Wyłomańska, A. Chechkin: Multifractional Brownian motion with telegraphic, stochastically varying exponent, submitted, 2024