Photo by tamiminaser from unsplash
ABSTRACT Functional data analysis has emerged as a new area of statistical research with a wide range of applications. In this paper, we propose novel models based on wavelets for… Click to show full abstract
ABSTRACT Functional data analysis has emerged as a new area of statistical research with a wide range of applications. In this paper, we propose novel models based on wavelets for spatially correlated functional data. These models enable one to regularize curves observed over space and predict curves at unobserved sites. We compare the performance of these Bayesian models with several priors on the wavelet coefficients using the posterior predictive criterion. The proposed models are illustrated in the analysis of porosity data.
Keywords:
bayesian models;
correlated curves;
spatially correlated;
predicting spatially;
hierarchical bayesian;
models predicting
Journal Title: Statistics
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!
Journal Title: Statistics
Year Published: 2018
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!