Time series, wavelets, high dimensional data and applications

• Grant number: 23/02538-0
• Support Opportunities: Research Projects - Thematic Grants
• Start date: September 01, 2023
• End date: August 31, 2028
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Statistics
• Principal Investigator: Aluísio de Souza Pinheiro
• Grantee: Aluísio de Souza Pinheiro
• Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Pesquisadores principais: Hedibert Freitas Lopes ; Luiz Koodi Hotta ; Pedro Alberto Morettin ; Ronaldo Dias
• Associated researchers: Airlane Pereira Alencar ; Alejandro César Frery Orgambide ; Audrone Virbickaite ; Carlos Cesar Trucios Maza ; Carlos Marinho Carvalho ; Chang Chiann ; Guilherme Vieira Nunes Ludwig ; João Ricardo Sato ; Márcio Poletti Laurini ; Mauricio Enrique Zevallos Herencia ; Michel Helcias Montoril ; Paulo Cilas Marques Filho ; Rodney Vasconcelos Fonseca ; Rogério Galante Negri
• Associated research grant(s): 25/02138-7 - Time Series Analyses: Time Domain, Spectral Analysis and Cpestral Analysis, AV.BR; 24/05242-7 - MATRIX Workshop - Multivariate Dependence Modeling: Theory and Applications, AR.EXT
• Associated scholarship(s): 25/08017-7 - Wavelet Clustering and Classification, BP.IC; 25/07456-7 - Estimation and Forecasting in High-Dimensional Dynamic Factor Models in the Presence of Outliers, BP.IC; 25/06681-7 - Bayesian Modeling of Multivariate Integer-valued Autoregressive Processes, BP.PD; + associated scholarships 25/08612-2 - Computational methods for approximated inference in Poisson spatial regression, BP.IC; 24/22101-8 - Clustering and feature screening in Functional regression model by Variational Inference., BP.PD; 24/23204-5 - Shape-preserving estimators of copulas, BP.PD; 24/20120-5 - Deep learning methodologies for change detection in SAR image time series, BP.DD; 24/21327-2 - Robust estimation of high-dimensional volatility models with and without regime changes, BP.PD; 24/18134-8 - Selective inference for high-dimensional data, BP.PD; 23/18036-3 - Hierarchical Bayesian model for predicting spatially correlated curves and with non-equidistant spacing, BP.PD; 24/01480-0 - Modeling and forecasting financial time series through hybrid methodologies, BP.DR; 24/08171-3 - Study of Robustness of Some Methods Applied to Financial Time Series, BP.IC; 24/07656-3 - Time Series and Machine Learning, BP.IC; 24/06269-6 - Assessing backtesting tools for Value-at-Risk and expected shortfall, BP.IC; 24/01079-4 - Financial long-term risk estimation in Brazilian stocks, BP.IC; 23/14505-9 - Change detection on SAR images time series via machine learning, BP.IC; 23/12361-0 - Wavelet Covariate Screening. Applications in High Dimensional Data Analysis., BP.IC; 23/12400-5 - Wavelet Analysis of Functional Data - Applications in Econometrics, BP.IC; 23/11547-2 - Factor models with vector autoregressive dynamics, BP.DD - associated scholarships

Abstract

This project is a natural follow-up to an ongoing project 18/04654-9, which is the most recent of a series of thematic projects from this research group endowed by FAPESP in the last twenty years. The proposed statistical methodologies will have application in Medicine, Finance, Biology, Physics, Neurosciences, Engineering, among others areas. They solve theoretical and empirical questions, in the following topics, in a mostly interwoven manner: (1) Generalizations of ARMA, processes, (2) Wavelet methods, (3) Quasi U-statistics, (4) Extreme values in time series, (5) Volatility modeling in financial data, including high-frequency data, (6) Functional data analysis, (7) high dimensional data, with focus on time series, spacial-temporal data, financial series, satellite image analysis, genetics, MRI and fNRIS. Besides the scientific output on the form of published papers in highly selective international journals and presentation in international meetings, the project should result in highly skilled young researchers, through post-doctoral, doctoral, masters, and undergraduate work supervisions. In order to ascertain the state-of-the-art status of the aforementioned research, periodical seminars and annual internationals workshops will be held, as well as visits from the Brazilian team members to world centers, and to the Brazilian institutions by international research leaders. (AU)

Scientific publications

(17)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

BIAZOLI JR, CLAUDINEI E.; SATO, JOAO R.; PLUESS, MICHAEL. Causal Relationships in Longitudinal Observational Data: An Integrative Modeling Approach. PSYCHOLOGICAL METHODS, v. N/A, p. 17-pg., 2024-04-22. (23/02538-0, 18/21934-5)

CONSOLI, RODRIGO A.; COLLI, EDUARDO; SOARES JR, RAIMUNDO DA SILVA SOARES; SATO, JOAO R.; MARSON, GUILHERME A.. Three-Dimensional Mapping of the Rotation of Interactive Virtual Objects with Eye-Tracking Data. JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, v. N/A, n. 212, p. 26-pg., 2024-10-01. (23/02538-0, 18/21934-5, 18/04654-9)

ROCHA, GABRIEL SIFUENTES; LAURINI, MARCIO POLETTI. Lottery stocks in Brazil: investigating risk premium and investor behavior. REVIEW OF BEHAVIORAL FINANCE, v. 16, n. 6, p. 20-pg., 2024-09-12. (23/02538-0)

MARQUES, F. PAULO C.. Universal distribution of the empirical coverage in split conformal prediction. Statistics & Probability Letters, v. 219, p. 5-pg., 2025-01-04. (23/02538-0)

SOARES, RAIMUNDO DA SILVA; PINHEIRO, ENEYSE DAYANE; OKU, AMANDA YUMI AMBRIOLA; RIZZO, MARILIA BISCAIA; VIEIRA, CAROLINNE DAS NEVES; SATO, JOAO RICARDO. Integrating Students' Real-Time Gaze in Teacher-Student Interactions: Case Studies on the Benefits and Challenges of Eye Tracking in Primary Education. APPLIED SCIENCES-BASEL, v. 14, n. 23, p. 17-pg., 2024-12-01. (23/18337-3, 23/12217-6, 21/05332-8, 23/02538-0)

SOARES JR, RAIMUNDO DA SILVA; OKU, AMANDA YUMI AMBRIOLA; BARRETO, CANDIDA S. F.; SATO, JOAO RICARDO. Exploring neural efficiency in spatial cognition: A comparative study of 3D visual stimuli in virtual reality across STEM and non-STEM fields. Behavioural Brain Research, v. 477, p. 9-pg., 2024-10-19. (23/16997-6, 21/05332-8, 18/04654-9, 19/17907-5, 18/21934-5, 23/02538-0, 23/13418-5)

NEGRI, ROGERIO G.; FRERY, ALEJANDRO C.; CASACA, WALLACE; GAMBA, PAOLO; BHATTACHARYA, AVIK. Unsupervised Multitemporal Triclass Change Detection. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, v. 62, p. 17-pg., 2024-01-01. (21/01305-6, 23/02538-0, 21/03328-3)

PINTO, MATEUS GONZALEZ DE FREITAS; CHIANN, CHANG. A maximum-likelihood-based approach to estimate the long memory parameter using fractional spline wavelets. Signal Processing, v. 222, p. 11-pg., 2024-05-02. (23/02538-0, 18/04654-9)

LUDWIG, GUILHERME; WANG, YUAN; CHU, TINGJIN; WANG, HAONAN; ZHU, JUN. Bayesian analysis and variable selection for spatial count data with an application to Rio de Janeiro gun violence. SPATIAL STATISTICS, v. 67, p. 17-pg., 2025-02-28. (23/02538-0, 18/04654-9)

RECACHO, VITOR; LAURINI, MARCIO P.. Bayesian structural decomposition of streamflow time series. Journal of Hydrology, v. 649, p. 17-pg., 2024-12-10. (23/02538-0)

FRANCO, JOAO PEDRO M.; LAURINI, MARCIO. Multivariate Risk Analysis in Cryptocurrency Market: An Optimal Transport Approach. COMPUTATIONAL ECONOMICS, v. N/A, p. 42-pg., 2025-02-15. (23/02538-0)

BOARETTO, GILBERTO; LAURINI, MARCIO POLETTI. DSGE Estimation Using Generalized Empirical Likelihood and Generalized Minimum Contrast. Entropy, v. 27, n. 2, p. 36-pg., 2025-02-01. (23/02538-0)

CHAIM, PEDRO; LAURINI, MARCIO POLETTI. Bayesian Inference for Long Memory Stochastic Volatility Models. ECONOMETRICS, v. 12, n. 4, p. 28-pg., 2024-12-01. (23/02538-0)

SATO, JOAO RICARDO; GIANLORENCO, ANNA CAROLYNA; FERNANDES, ELAYNE BORGES; DA ROCHA, THALITA FRIGO; MAKIYAMA, ANTONIO MASSATO; DIPIETRO, LAURA. An Experiment Using Functional Near-Infrared Spectroscopy and Robot-Assisted Multi-Joint Pointing Movements of the Lower Limb. JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, v. N/A, n. 208, p. 19-pg., 2024-06-01. (18/09559-4, 21/05332-8, 18/04654-9, 18/21934-5, 23/02538-0)

BRANCO, RAFAEL R.; RUBESAM, ALEXANDRE; ZEVALLOS, MAURICIO. Forecasting realized volatility: Does anything beat linear models?. JOURNAL OF EMPIRICAL FINANCE, v. 78, p. 22-pg., 2024-06-26. (23/02538-0, 18/04654-9)

XIAN, CHENGQIAN; DE SOUZA, CAMILA P. E.; JEWELL, JOHN; DIAS, RONALDO. Clustering functional data via variational inference. Advances in Data Analysis and Classification, v. N/A, p. 50-pg., 2024-04-30. (23/02538-0)

SIMIS, MARCEL; MARQUES, LUCAS MURRINS; BARBOSA, SARA PINTO; SUGAWARA, ANDRE TADEU; SATO, JOAO RICARDO; PACHECO-BARRIOS, KEVIN; BATTISTELLA, LINAMARA RIZZO; FREGNI, FELIPE. Distinct patterns of metabolic motor cortex activity for phantom and residual limb pain in people with amputations: A functional near-infrared spectroscopy study. NEUROPHYSIOLOGIE CLINIQUE-CLINICAL NEUROPHYSIOLOGY, v. 54, n. 1, p. 8-pg., 2024-02-20. (20/08512-4, 17/12943-8, 21/05897-5, 21/05332-8, 18/04654-9, 18/21934-5, 23/02538-0)