An analysis and forecast of LRT demand using Arima models

• Main Authors: Resultay, Nino Andrew, Tan, Jimmy
• Format: text
• Language: English
• Published: Animo Repository 1996
• Subjects: Mathematical models; Computer programs; Transportation; Light Rail Transit (LRT); Time-series analysis
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/16348
• Institution: De La Salle University

This thesis is about forecasting LRT demand using the Univariate Box-Jenkins ARIMA models. It is a requirement in forecasting that the data must be stationary. Nonstationary data can be converted into a stationary data by differencing. There are four common processes used in forecasting these are Au...