Project 1: The dataset consists of monthly observations from Mauna Loa, Hawaii. I estimated different linear models (OLS, WLS, local linear trend) for the development of atmospheric CO2 over the past 50 years and predicted the concentration a couple of years ahead
Project 2: Its purpose is to understand ARMA Processes and Seasonal Processes. I predicted the number of sales of apartments using a model of the quarterly number of sales of apartments in the capital region of Denmark.
Project 3: The same dataset from project 1 but this time I implemented an ARIMA model and the goal was always to predict the concentration in the coming years.
Project 4: the dataset was related to water characteristics. The task was to model the dissolved oxygen in water and to predict the water salinity using Kalman filter.