Time Series Analysis and Forecasting (using ARIMA, UCM and Random Forest models) of a restaurant's revenue during the first lockdown of the COVID-19 pandemic in Italy, to estimate the loss incurred.
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Updated
Mar 1, 2023 - R
Time Series Analysis and Forecasting (using ARIMA, UCM and Random Forest models) of a restaurant's revenue during the first lockdown of the COVID-19 pandemic in Italy, to estimate the loss incurred.
Tetuan City Electricity Consumption High-Frequency Time-Series Forecasting Using Arima, UCM, Machine Learning (Random Forest and k-NN), and Deep Learning (GRU Recurrent Neural Network) Models.
I have performed a time series analysis of the stock prices of Tata Consultancy Services from 2002 to 2021. I have started by visualising the data. And then I fitted models like an autoregressive integrated moving average (ARIMA) model, Vector autoregression (VAR), SARIMA (seasonal ARIMA) model, UCM, and Dynamic Factor models.
High-frequency time series forecast of electricity consumptions using ARIMA, UCM and ML techniques
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