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020 _a9783031663987
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024 7 _a10.1007/978-3-031-66398-7
_2doi
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072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
245 1 0 _aTime Series and Wavelet Analysis
_h[electronic resource] :
_bFestschrift in Honor of Pedro A. Morettin /
_cedited by Chang Chiann, Aluisio de Souza Pinheiro, Clélia Maria Castro Toloi.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXXI, 293 p. 77 illus., 66 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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505 0 _a- Part I Time Series and Econometrics -- Analysis of High-Frequency Seasonal Time Series -- Stochastic Volatility With Feedback -- Structural Breaks and Common Factors -- A Note About Calibration Tests for VaR and ES -- Dynamic Ordering Learning in Multivariate Forecasting -- A Generalization of the Ornstein-Uhlenbeck Process: Theoretical Results, Simulations and Estimation -- Does the Private Database Help to Explain Brazilian Inflation? -- Identifiability and Whittle Estimation of Periodic ARMA Models -- Dynamic Factor Copulas for Minimum-CVaR Portfolio Optimization -- Part II Wavelets -- Does White Noise Dream of Square Waves?: A Matching Pursuit Conundrum -- Robust Wavelet-based Assessment of Scaling with Applications -- An Overview of Spectral Graph Wavelets -- Statistical Inferences on Brain Functional Networks Using Graph Theory and Multivariate Wavestrapping: An fNIRS Hyperscanning Illustration -- UtilizingWavelet Transform in the Analysis of Scaling Dynamics for Milk Quality Evaluation -- Wavelet Estimation of Nonstationary Spatial Covariance Function.
520 _aProf. Pedro A. Morettin is a Distinguished Professor of Statistics at the Institute of Mathematics and Statistics of the University of São Paulo (IME-USP), where he has built an academic career spanning almost six decades. His work has had a significant impact on Time Series Analysis and Wavelet Statistical Methods, as exemplified by the papers appearing in this Festschrift, which are authored by renowned researchers in both fields. Besides his long-term commitment to research, Prof. Morettin is very active in mentoring and serving the profession. Moreover, he has written several textbooks, which are still a leading source of knowledge and learning for undergraduate and graduate students, practitioners, and researchers. Divided into two parts, the Festschrift presents a collection of papers that illustrate Prof. Morettin’s broad contributions to Time Series and Econometrics, and to Wavelets. The reader will be able to learn state-of-the-art statistical methodologies, from periodic ARMA models, fractional Brownian motion, and generalized Ornstein-Uhlenbeck processes to spatial models, passing through complex structures designed for high-dimensional data analysis, such as graph and dynamic models. The topics and data features discussed here include high-frequency sampling, fNRIS, forecasting, portfolio apportionment, volatility assessment, dairy production, and inflation, which are relevant to econometrics, medicine, and the food industry. The volume ends with a discussion of several very powerful tools based on wavelets, spectral analysis, dimensionality reduction, self-similarity, scaling, copulas, and other notions.
650 0 _aTime-series analysis.
650 0 _aBiometry.
_965981
650 0 _aStatistics .
_965982
650 1 4 _aTime Series Analysis.
650 2 4 _aBiostatistics.
_965985
650 2 4 _aStatistics in Business, Management, Economics, Finance, Insurance.
_969738
700 1 _aChiann, Chang.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_989224
700 1 _ade Souza Pinheiro, Aluisio.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_989225
700 1 _aCastro Toloi, Clélia Maria.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_989226
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031663970
776 0 8 _iPrinted edition:
_z9783031663994
776 0 8 _iPrinted edition:
_z9783031664007
856 4 0 _uhttps://doi.org/10.1007/978-3-031-66398-7
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