Reconstruction of NDVI Data with Normal Variance-Mean Mixture Noise using Stochastic Gradient Methods
Satellite data is useful for making inference on large areas, but there are plenty of problems associated with the technology. The observation errors need to be carefully modelled in order to make inference from the data. In addition, the large data-sets involved makes straight-forward computations infeasible. This thesis explores a non-Gaussian noise structure, and implements a modified EM algorit
