Robust interpolation of sequences with periodically stationary multiplicative seasonal increments


  • M.M. Luz BNP Paribas Cardif, 8 Illinska str., 04070, Kyiv, Ukraine
  • M.P. Moklyachuk Taras Shevchenko National University, 64/13 Volodymyrska str., 01601, Kyiv, Ukraine


periodically stationary increment, SARFIMA, fractional integration, filtering, optimal linear estimate, mean square error, least favourable spectral density matrix, minimax spectral characteristic
Published online: 2022-06-13


We consider stochastic sequences with periodically stationary generalized multiple increments of fractional order which combines cyclostationary, multi-seasonal, integrated and fractionally integrated patterns. We solve the interpolation problem for linear functionals constructed from unobserved values of a stochastic sequence of this type based on observations of the sequence with a periodically stationary noise sequence. For sequences with known matrices of spectral densities, we obtain formulas for calculating values of the mean square errors and the spectral characteristics of the optimal interpolation of the functionals. Formulas that determine the least favorable spectral densities and the minimax (robust) spectral characteristics of the optimal linear interpolation of the functionals are proposed in the case where spectral densities of the sequences are not exactly known while some sets of admissible spectral densities are given.

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How to Cite
Luz, M.; Moklyachuk, M. Robust Interpolation of Sequences With Periodically Stationary Multiplicative Seasonal Increments. Carpathian Math. Publ. 2022, 14, 105-126.