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Statistics
A Journal of Theoretical and Applied Statistics
Volume 49, 2015 - Issue 1
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Original Articles

Estimation of harmonic component in regression with cyclically dependent errors

A.V. IvanovNational Technical University ‘Kyiv Polytechnic Institute’, 37 Peremogy Ave, 03056Kyiv, Ukraine
,
N.N. LeonenkoSchool of Mathematics, Cardiff University, Senghennydd Road, CardiffCF24 4YH, UK
,
M.D. Ruiz-MedinaDepartment of Statistics and Operations Research, University of Granada, Campus Fuente Nueva s/n, E-18071Granada, SpainCorrespondence[email protected]
&
B.M. ZhurakovskyNational Technical University ‘Kyiv Polytechnic Institute’, 37 Peremogy Ave, 03056Kyiv, Ukraine
Pages 156-186 | Received 30 Oct 2013, Accepted 06 Nov 2013, Published online: 10 Jan 2014

Citations (12)

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Vo Anh, Andriy Olenko & Volodymyr Vaskovych. (2019) On LSE in regression model for long-range dependent random fields on spheres. Statistics 53:5, pages 1131-1151.
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Articles from other publishers (11)

Hojun You, Kyubaek Yoon, Wei-Ying Wu, Jongeun Choi & Chae Young Lim. (2024) Regularized nonlinear regression with dependent errors and its application to a biomechanical model. Annals of the Institute of Statistical Mathematics 76:3, pages 481-510.
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Alexander Ivanov & Viktor Hladun. (2024) Asymptotic normality of the LSE for chirp signal parameters. Modern Stochastics: Theory and Applications, pages 195-216.
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A. V. Ivanov & I. V. Orlovskyi. (2023) Detection of hidden periodicities in models with discrete time and long range dependent random noise. Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics:1, pages 48-58.
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Oleksandr Dykyi & Alexander Ivanov. (2023) Consistency of LSE for the many-dimensional symmetric textured surface parameters. Modern Stochastics: Theory and Applications, pages 267-285.
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Alexander Ivanov & Kateryna Moskvychova. (2020) Asymptotic normality of the residual correlogram in the continuous-time nonlinear regression model. Modern Stochastics: Theory and Applications, pages 93-113.
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A. Ivanov & I. Savych. (2021) On the least squares estimator asymptotic normality of the multivariate symmetric textured surface parameters. Theory of Probability and Mathematical Statistics 105:0, pages 151-169.
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A. V. Ivanov, N. N. Leonenko & I. V. Orlovskyi. (2019) On the Whittle estimator for linear random noise spectral density parameter in continuous-time nonlinear regression models. Statistical Inference for Stochastic Processes 23:1, pages 129-169.
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T. O. Drabyk & O. V. Ivanov. (2019) Asymptotic normality of the least squares estimate in trigonometric regression with strongly dependent noise. Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics:4, pages 24-41.
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O. V. Ivanov & I. V. Orlovs’kyi. (2017) Asymptotic Properties of the M-Estimates of Parameters in a Nonlinear Regression Model with Discrete Time and Singular Spectrum. Ukrainian Mathematical Journal 69:1, pages 32-61.
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G. D. Bila. (2016) Identification of a Nonparametric Signal Under Strongly Dependent Random Noise. Cybernetics and Systems Analysis 52:1, pages 160-172.
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O. V. Ivanov & K. K. Moskvychova. (2014) Asymptotic Expansion of the Moments of Correlogram Estimator for the Random-Noise Covariance Function in the Nonlinear Regression Model. Ukrainian Mathematical Journal 66:6, pages 884-904.
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