| Chaotic signals inside some tick-by-tick financial time series JE Sandubete, L Escot Chaos, Solitons & Fractals 137, 109852, 2020 | 22 | 2020 |
| Solving the chaos model-data paradox in the cryptocurrency market L Pietrych, JE Sandubete, L Escot Communications in Nonlinear Science and Numerical Simulation 102, 105901, 2021 | 19 | 2021 |
| Measuring the candidates' emotions in political debates based on facial expression recognition techniques A Rodríguez-Fuertes, J Alard-Josemaría, JE Sandubete Frontiers in Psychology 13, 785453, 2022 | 13 | 2022 |
| DChaos: Chaotic time series analysis JE Sandubete, L Escot R package version 0.1-5 (last version, 2020 | 10 | 2020 |
| Estimating Lyapunov exponents on a noisy environment by global and local Jacobian indirect algorithms L Escot, JE Sandubete Applied Mathematics and Computation 436, 127498, 2023 | 8 | 2023 |
| Back to Basics: The Power of the Multilayer Perceptron in Financial Time Series Forecasting A Lazcano, MA Jaramillo-Morán, JE Sandubete Mathematics 12 (12), 1920, 2024 | 4 | 2024 |
| DChaos: an R package for chaotic time series analysis JE Sandubete Galán, L Escot Mangas R Foundation for Statistical Computing, 2021 | 4 | 2021 |
| EMDFormer model for time series forecasting AL de Rojas, MA Jaramillo-Morán, JE Sandubete AIMS Mathematics 9 (4), 9419-9434, 2024 | 2 | 2024 |
| Testing the efficient market hypothesis and the model-data paradox of chaos on top currencies from the foreign exchange market (FOREX) JE Sandubete, L Beleña, JC García-Villalobos Mathematics 11 (2), 286, 2023 | 2 | 2023 |
| Quantifying chaos from time-series data through Lyapunov exponents: a computational data science approach JE Sandubete Galán Universidad Complutense de Madrid, 2021 | 1 | 2021 |
| Walking Back the Data Quantity Assumption to Improve Time Series Prediction in Deep Learning A Lazcano, P Hidalgo, JE Sandubete Applied Sciences 14 (23), 11081, 2024 | | 2024 |
| Detecting Structural Changes in Time Series by Using the BDS Test Recursively: An Application to COVID-19 Effects on International Stock Markets L Escot, JE Sandubete, Ł Pietrych Mathematics 11 (23), 4843, 2023 | | 2023 |
| Package ‘DChaos’ JE Sandubete, L Escot, MJE Sandubete | | 2023 |
| Estimating Lyapunov exponents on a noisy environment by global and local Jacobian indirect algorithms L Escot Mangas, JE Sandubete Galán Elsevier, 2023 | | 2023 |
| ANALYSIS OF THE IMPACT OF THE TEACHER’S PRESENCE IN AN ONLINE TRAINING SESSION ON STUDENTS USING THE EYE TRACKING TECHNIQUE JE Sandubete, A Rodríguez-Fuertes, P Reinares-Lara ICERI2022 Proceedings, 4629-4638, 2022 | | 2022 |
| Ampliación del proyecto R-adaptación de la asignatura de Métodos Econométricos en Economía y Finanzas del Grado de Estadística Aplicada L Escot Mangas, A Pérez Alonso, JL Brita-Paja Segoviano, ... eprints UCM, 2021 | | 2021 |
| R-adaptación de la asignatura de métodos econométricos en economía y finanzas del Grado de Estadística Aplicada L Escot Mangas, A Pérez Alonso, JL Brita Paja, MR Ferrán Aranaz, ... | | 2020 |
| Quantifying chaos from time-series data through lyapunov exponents: a computational data science approach/cuantificando el caos en series temporales a través del exponente de … JE Sandubete Galan Quantifying chaos from time-series data through lyapunov exponents: a …, 2020 | | 2020 |
| Chaotic signals inside some tick-by-tick financial time series JE Sandubete Galán, L Escot Mangas Elsevier, 2020 | | 2020 |
| Quantifying chaos from time-series data through lyapunov exponents: a computational data science approach/cuantificando el caos en series temporales a través del exponente de … JES Galan Universidad Complutense de Madrid, 2020 | | 2020 |
