Applied Time Series Analysis and Forecasting with Python, 1st ed. 2022 Statistics and Computing Series
Auteurs : Huang Changquan, Petukhina Alla
Alla Petukhina is a Lecturer at the School of Computing, Communication and Business, HTW Berlin, Germany. She was a postdoctoral researcher at the School of Business and Economics at the Humboldt-Universität zu Berlin, where she obtained her PhD in Statistics in 2018. Her research interests include asset allocation strategies, regression shrinkage techniques, quantiles and expectiles, history of statistics and investment strategies with crypto-currencies.
Presents methods and applications of time series analysis and forecasting using Python
Addresses common statistical methods as well as modern machine learning procedures
Provides a step-by-step demonstration of the Python code, and exercises for each chapter
Date de parution : 10-2023
Ouvrage de 372 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 26,59 €
Ajouter au panierDate de parution : 10-2022
Ouvrage de 372 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 105,49 €
Ajouter au panierThèmes d’Applied Time Series Analysis and Forecasting with Python :
Mots-clés :
Time Series Analysis; Python; Forecasting; Big Data Analysis; Data Visualization; Machine Learning for Time Series; Artificial Intelligence; Stationary Time Series; Nonstationary Time Series; Multivariate Time Series; Financial Time Series; State Space Models; Markov Switching Models; ARMA and ARIMA; Data Science