This project analyzes daily vehicle traffic data from the Baregg Tunnel (November 2003 – November 2005) to determine how accurately daily traffic can be forecasted. The objective is to compare a simple benchmark model (Naïve) against a more structured approach using Linear Regression with trend and weekly seasonality. The data are partitioned into a training period (Nov 2003 – Jun 2005) and a validation period (Jul 2005 – Nov 2005) to evaluate out-of-sample forecast accuracy. Model performance is assessed using standard metrics including ME, RMSE, MAE, MAPE, and MASE. Diagnostic plots are also used to evaluate residual behavior and check for remaining autocorrelation. Results show that incorporating trend and weekly seasonality significantly improves forecast accuracy compared to the Naïve benchmark. The Linear Regression model better captures systematic traffic patterns and produces more reliable daily forecasts. This analysis demonstrates how time series modeling techniques can be applied to real-world transportation data to support forecasting and operational planning decisions.

Bellabeat es una empresa de alta tecnología que fabrica productos de bienestar enfocados en mujeres. Fundada en 2013 por Urška Sršen y Sando Mur, la compañía ha crecido rápidamente posicionándose como líder en wellness tech para mujeres.

Aplicación de técnicas de análisis multivariado (PCA, Clustering y MCA) para la evaluación estratégica del mercado inmobiliario urbano.

Un análisis de las condiciones de vivienda y población de las localidades del municipio de Mier y Noriega en Nuevo León.

Aplicación de técnicas de análisis multivariado (PCA, Clustering y MCA) para la evaluación estratégica del mercado inmobiliario urbano.

PRONOSTICO PRECIPITACIÓN Y TEMPERATURA