Exploring probabilistic time series methods for electricity demand forecasting

Time Series Forecasting of the Multivariate El Niño-Southern Oscillation (ENSO) Using ARIMA Models.

The project aims to apply deep learning and statistical models to historical market data to accurately predict stock prices

This is my portfolio.

This project describes the step-by-step method for forecasting the mean temperature of Spain through the application of various predictive methods (ARIMA, SARIMA, SARIMAX y PROPHET).

Aplicación de la Metodología Box-Jenkins que pretende mostrar una herramienta estadística de análisis univariante para la predicción de una empresa que cotice en un mercado continuo y el precio objetivo de la compañía, es decir, su acción.

Website with LSTM model to predict Singapore's temperature

This project aims at studying temporal behaviour of smartphone app users, with special focus at changes in usage. The analysis will rely on time series techniques to detect change points and forecast shifts in usage. In particular, we will leverage univariate timeseries approaches.

Code for the Lancet Digital Health manuscript

forecasting electricity demand for the next 1-2 years using historical monthly consumption data and various forecasting models.

This repository contains a research paper I completed for my Time Series Econometrics class.

This software was designed with the purpose of anomaly detection and correction for time series water sensor data. This software was developed using the Logan River Observatory data set.

The repository gives case studies on short-term traffic flow forecasting strategies within the scope of my master thesis.

A demand forecasting model for an E-Commerce retailer, built using KPIs from Google Analytics & implemented in RStudio. Models: time-series, ARIMA, Regression (multivariate & dynamic). Open-source & contributions welcome.

Database management and data analytics from a car-sharing dataset. The dataset contains information about the customers' demand rate between January 2017 and August 2018.

This is a release of data and analysis scripts of the "Associations of inclement weather and poor air quality with non-motorized trail volumes" paper published in Transportation Research Part D.

Tesla Stock Price Prediction using the techniques like Feature Extraction, Feature Importance, ARIMA, SARIMAX, Fourier Transform. Forecasting the future price of the Tesla Stock Price.